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soorena62
2026-02-08 04:38:10 +03:30
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Galaxy/README.md
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# Galaxy Project
This folder contains prototypes and files related to the **Galaxy Workflow Engine**.
The goal of this section is to define and run simple workflows to demonstrate Galaxy's capabilities in managing and reproducing scientific processes.
## Quick Start
To run a sample workflow:
1. Prepare a workflow file (e.g. `workflow.xml`).
2. Run Galaxy and load the workflow.
## Folder Structure
- `workflow.xml`: A prototype of a simple workflow
- Other tools and supporting files will be added in the future
## Description
Galaxy is a powerful platform for performing scientific and data analytics. In this project, we use it to create reproducible and auditable workflows.
Galaxy/docker-compose.yml
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version: "3.9"
services:
galaxy:
image: quay.io/bgruening/galaxy:24.2
container_name: galaxy_radiuma
ports:
- "8080:80" # رابط وب Galaxy
environment:
- GALAXY_CONFIG_BRAND=Radiuma Galaxy
- GALAXY_CONFIG_ADMIN_USERS=admin@radiuma.org
- GALAXY_CONFIG_REQUIREMENTS_FILE=/galaxy/config/requirements.txt
- GALAXY_CONFIG_BOOTSTRAP_ADMIN_API_KEY=radiuma_admin_key # ✅ جایگزین master_api_key
- GALAXY_CONFIG_ENABLE_FTP_UPLOAD_DIR=True
- GALAXY_CONFIG_FTP_UPLOAD_DIR=/ftp_uploads # ✅ مسیر داخلی FTP
- GALAXY_CONFIG_TOOL_CONFIG_FILE=/galaxy/config/tool_conf.xml
- GALAXY_CONFIG_LOG_LEVEL=DEBUG
- GALAXY_CONFIG_WATCH_TOOLS=False
- GALAXY_CONFIG_DATABASE_CONNECTION=postgresql://galaxy:galaxy@postgres:5432/galaxy
volumes:
- galaxy_data:/galaxy/database
- ./galaxy/tools:/galaxy/tools
- ./requirements.txt:/galaxy/config/requirements.txt
- ./galaxy/config/tool_conf.xml:/galaxy/config/tool_conf.xml
- ./ftp:/ftp_uploads # ✅ mount صحیح برای FTP
restart: unless-stopped
depends_on:
postgres:
condition: service_healthy
postgres:
image: postgres:15
container_name: galaxy_postgres
environment:
POSTGRES_USER: galaxy
POSTGRES_PASSWORD: galaxy
POSTGRES_DB: galaxy
volumes:
- ./galaxy_db:/var/lib/postgresql/data
restart: unless-stopped
healthcheck:
test: ["CMD", "pg_isready", "-U", "galaxy", "-h", "postgres"]
interval: 10s
timeout: 5s
retries: 5
volumes:
galaxy_data:
Galaxy/galaxy/config/tool_conf.xml
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<section id="radiuma" name="Radiuma Tools">
<tool file="radiuma/radiomics.xml"/>
<tool file="radiuma/preprocessing.xml"/>
<tool file="radiuma/classification.xml"/>
</section>
Galaxy/galaxy/tools/pysera_tool.xml
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<tool id="pysera_radiomics" name="PySERA Radiomics Extraction" version="2.1.2">
<description>Standardized radiomics feature extraction using PySERA</description>
<command><![CDATA[
python3 -m pysera \
--image-input "$image_input" \
--mask-input "$mask_input" \
--output "$output"
]]></command>
<inputs>
<param name="image_input" type="data" label="Medical Image (NIfTI/DICOM)" />
<param name="mask_input" type="data" label="Segmentation Mask" />
</inputs>
<outputs>
<data name="output" format="csv" label="Extracted Radiomics Features" />
</outputs>
<help><![CDATA[
This tool uses PySERA (Python Standardized Extraction for Radiomics Analysis)
for IBSI-compliant radiomics feature extraction.
]]></help>
</tool>
Galaxy/galaxy/tools/radiuma/classification.xml
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<param name="algorithm" type="select" label="Classifier">
<option value="LogisticRegression">Logistic Regression</option>
<option value="KNeighborsClassifier">KNN</option>
<option value="AdaBoostClassifier">AdaBoost</option>
<option value="BaggingClassifier">Bagging</option>
</param>
Galaxy/galaxy/tools/radiuma/classifiers.py
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Galaxy/galaxy/tools/radiuma/preprocessing.py
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from sklearn.utils import resample, shuffle
class preprocessing:
def __init__(self,X):
self.X = X
# def SelectAlg(self):
# import json
# f = open('data.json')
# JSONdata = json.load(f)
# f.close()
# algn = self.AlgName
# if self.AlgName == "resample":
# self.Vs_resample(
# JSONdata[algn][0],
# JSONdata[algn][1]
# )
# elif self.AlgName == "shuffle":
# self.Vs_shuffle(
# JSONdata[algn][0],
# JSONdata[algn][1]
# )
# else:
# print("Algorithm name is wrong")
def Vs_resampling(self,str=False,rep=False):
if str:
x2 = resample(self.X , replace=rep)
else:
x2 = resample(self.X , replace=rep)
return x2
def Vs_shuffling(self):
x2 = shuffle(self.X)
return x2
Galaxy/galaxy/tools/radiuma/preprocessing.xml
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<tool id="radiuma_preprocessing" name="Preprocessing" version="1.0.0">
<command>python3 $__tool_directory__/preprocessing.py --input $input --method $method --output $output</command>
<inputs>
<param name="input" type="data" format="csv" label="Input Features"/>
<param name="method" type="select" label="Method">
<option value="resample">Resample</option>
<option value="shuffle">Shuffle</option>
</param>
</inputs>
<outputs>
<data name="output" format="csv" label="Processed Features"/>
</outputs>
</tool>
Galaxy/galaxy/tools/radiuma/radiomics.py
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import tkinter as tk
from tkinter import ttk, messagebox
from tkinter.filedialog import askopenfilename, askdirectory
from PIL import Image, ImageTk
from prompt_toolkit.data_structures import Point
def radiomics_feature_generator_view(self, oid):
def _validate(P, mi, ma):
if P == "":
P = mi
if P.count(".") > 1:
return False
P = P.replace(".", "")
return P.isdigit() and float(P) >= float(mi) and float(P) <= float(ma)
def _validate_c(P, mi, ma):
if P == "":
P = mi
items = P.split(",")
for i in items:
if i.count(".") > 1:
return False
j = i.replace(".", "")
if j == '':
j = '0'
i = '0.'
if not (j.isdigit() and float(i) >= float(mi) and float(i) <= float(ma)) and i != "":
return False
return True
def _validate_int(P, mi, ma):
if P == "":
P = mi
try:
if P == '-':
P = '-1'
return int(P) >= int(mi) and int(P) <= int(ma)
except:
return False
self.arr_img = ImageTk.PhotoImage(Image.open("images/arrow-icon.png").resize((20, 20)))
main = self.newWindow
main.none = False
main.attributes('-toolwindow', True)
main.title('Radiomic Feature Generator')
main.resizable(False, False)
self.rbg = "#FFFFFF"
root = tk.Frame(main, bg=self.rbg)
# menu = tk.Frame(main, bg=self.bg)
root.grid(row=0, column=1)
# first row
# ttk.Separator(root, orient='horizontal').grid(column=0, row=0, columnspan=7, sticky="ew", padx=5, pady=5)
frame = tk.Frame(root, highlightthickness=2, highlightcolor="#D1CFE2", bg=self.rbg)
frame.grid(column=0, row=0, columnspan=6, sticky="news", padx=16, pady=(10, 5), ipady=2, ipadx=2)
tk.Label(frame, text="Source", bg=self.rbg, fg="#1C1C28").grid(column=0, row=0, sticky=tk.W, padx=5, pady=5)
self.ra_file_folder = tk.StringVar(value=0)
self.ra_file_folder.set(self.ras_file_folder[oid].get())
def select_radio(clean=True):
if self.ra_file_folder.get() == "0":
if clean:
if self.comp_conn[oid] == -1:
self.ra_file_slc_lbl.set("Select a file...")
self.ra_file_slc2_lbl.set("Select a file...")
elif self.comp_conn[oid] == 0 or self.comp_conn[oid] == 2:
self.ra_file_slc_lbl.set("Set by connection link")
self.ra_file_slc2_lbl.set("Select a file...")
else:
self.ra_file_slc_lbl.set("Select a file...")
self.ra_file_slc2_lbl.set("Set by connection link")
self.file_select = ""
self.file_slc_btn.config(image=self.slc_file_photo)
self.file_slc2_btn.config(image=self.slc_file_photo)
else:
if clean:
if self.comp_conn[oid] == -1:
self.ra_file_slc_lbl.set("Select a folder...")
self.ra_file_slc2_lbl.set("Select a folder...")
elif self.comp_conn[oid] == 0 or self.comp_conn[oid] == 2:
self.ra_file_slc_lbl.set("Set by connection link")
self.ra_file_slc2_lbl.set("Select a folder...")
else:
self.ra_file_slc_lbl.set("Select a folder...")
self.ra_file_slc2_lbl.set("Set by connection link")
self.file_select = ""
self.file_slc_btn.config(image=self.slc_folder_photo)
self.file_slc2_btn.config(image=self.slc_folder_photo)
tk.Radiobutton(frame, bg=self.rbg, text="Single file", variable=self.ra_file_folder, value=0,
command=select_radio).grid(column=1, row=0, padx=(0, 0))
tk.Radiobutton(frame, bg=self.rbg, text="Folder", variable=self.ra_file_folder, value=1, command=select_radio).grid(
column=1, row=0, padx=(150, 0))
tk.Label(frame, text="Original image", bg=self.rbg).grid(column=0, row=2, sticky=tk.W, padx=(5, 26), pady=5)
self.ra_file_slc_lbl = tk.StringVar(value="Select a file...")
if self.comp_conn[oid] == 0 or self.comp_conn[oid] == 2:
self.ra_file_slc_lbl.set("Set by connection link")
else:
t = self.ras_file_slc_lbl[oid].get()
if t.startswith("Set"):
if self.ras_file_folder[oid].get() == "0":
t = "Select a file..."
else:
t = "Select a folder..."
self.ra_file_slc_lbl.set(t)
ttk.Entry(frame, textvariable=self.ra_file_slc_lbl, state="disabled").grid(column=0, row=2, sticky="we",
padx=(100, 0), pady=5, ipady=10)
def select_file():
self.newWindow.attributes('-topmost', True)
if self.ra_file_folder.get() == "0":
self.file_select = askopenfilename(parent=root)
else:
self.file_select = askdirectory(parent=root)
self.newWindow.attributes('-topmost', False)
self.ra_file_slc_lbl.set(self.file_select)
self.slc_file_photo = tk.PhotoImage(file="images/file.png")
self.slc_folder_photo = tk.PhotoImage(file="images/folder.png")
self.file_slc_btn = tk.Button(frame, image=self.slc_file_photo, command=select_file, bg="#9CADCE", borderwidth=0,
height=40, width=40, state='disabled' if (
self.comp_conn[oid] == 0 or self.comp_conn[oid] == 2) else 'normal')
self.file_slc_btn.grid(column=0, row=2, sticky="w", padx=(220, 0))
tk.Label(frame, text="Region of interest (ROI)", bg=self.rbg).grid(column=1, row=2, sticky="e", padx=5, pady=5)
self.ra_file_slc2_lbl = tk.StringVar(value="Select a file...")
if self.comp_conn[oid] == 1 or self.comp_conn[oid] == 2:
self.ra_file_slc2_lbl.set("Set by connection link")
else:
t = self.ras_file_slc2_lbl[oid].get()
if t.startswith("Set"):
if self.ras_file_folder[oid].get() == "0":
t = "Select a file..."
else:
t = "Select a folder..."
self.ra_file_slc2_lbl.set(t)
ttk.Entry(frame, textvariable=self.ra_file_slc2_lbl, state="disabled").grid(column=2, row=2, sticky="we",
padx=(5, 0), pady=5, columnspan=2,
ipady=10, ipadx=4)
def select_file2():
self.newWindow.attributes('-topmost', True)
if self.ra_file_folder.get() == "0":
self.file_select2 = askopenfilename(parent=root)
else:
self.file_select2 = askdirectory(parent=root)
self.newWindow.attributes('-topmost', False)
self.ra_file_slc2_lbl.set(self.file_select2)
self.file_slc2_btn = tk.Button(frame, image=self.slc_file_photo, command=select_file2, bg="#9CADCE", borderwidth=0,
height=40, width=40, state='disabled' if (
self.comp_conn[oid] == 1 or self.comp_conn[oid] == 2) else 'normal')
self.file_slc2_btn.grid(column=7, row=2, sticky="w")
select_radio(False)
# ttk.Separator(root, orient='horizontal').grid(column=0, row=4, columnspan=7, sticky="ew", padx=5, pady=5)
frame = tk.Frame(root, highlightthickness=2, highlightcolor="#D1CFE2", bg=self.rbg)
frame.grid(column=0, row=4, columnspan=6, sticky="news", padx=16, pady=5, ipady=2, ipadx=2)
tk.Label(frame, text="Destination", bg=self.rbg, fg="#1C1C28").grid(column=0, row=4, sticky=tk.W, padx=5, pady=5)
self.ra_file_dest_lbl = tk.StringVar(value="Select a folder...")
self.ra_file_dest_lbl.set(self.ras_file_dest_lbl[oid].get())
ttk.Entry(frame, textvariable=self.ra_file_dest_lbl, state="disabled").grid(column=1, row=4, sticky="we",
padx=(5, 0), pady=5, columnspan=2,
ipady=10, ipadx=4)
def select_dest_folder():
self.newWindow.attributes('-topmost', True)
self.dest_select = askdirectory(parent=root)
self.newWindow.attributes('-topmost', False)
self.ra_file_dest_lbl.set(self.dest_select)
tk.Button(frame, image=self.slc_folder_photo, command=select_dest_folder, bg="#9CADCE", borderwidth=0, height=40,
width=40, ).grid(column=3, row=4, sticky="w")
# second tab
# ttk.Separator(root, orient='horizontal').grid(column=0, row=6, columnspan=7, sticky="ew", padx=5, pady=5)
frame = tk.Frame(root, highlightthickness=2, highlightcolor="#D1CFE2", bg=self.rbg)
frame.grid(column=0, row=6, columnspan=6, sticky="news", padx=16, pady=5, ipady=2, ipadx=2)
tk.Label(frame, text="Parameters", bg=self.rbg, fg="#1C1C28").grid(column=0, row=6, sticky=tk.W, padx=5, pady=5)
tk.Label(frame, bg=self.rbg,
text="Image modality type").grid(column=0,
row=7,
padx=3,
pady=3, sticky="w")
self.ra_rfg_imt_value = tk.StringVar(value="CT")
self.ra_rfg_imt_value.set(self.ras_rfg_imt_value[oid].get())
w = tk.OptionMenu(frame, self.ra_rfg_imt_value, "CT", "PET", "SPECT", "MR")
w.config(indicatoron=False, compound='right', image=self.arr_img)
w.config(highlightthickness=0, highlightbackground="black")
w.grid(column=1, row=7, padx=3, pady=3, sticky="we")
tk.Label(frame, bg=self.rbg,
text="Intensity outlier re-segmentatin flag").grid(column=2, row=7, padx=(20, 3), pady=3, sticky="w")
self.ra_rfg_iorf_value = tk.StringVar(value="0")
self.ra_rfg_iorf_value.set(self.ras_rfg_iorf_value[oid].get())
w = tk.OptionMenu(frame, self.ra_rfg_iorf_value, "0", "1")
w.config(indicatoron=False, compound='right', image=self.arr_img)
w.config(highlightthickness=0, highlightbackground="black")
w.grid(column=3,
row=7,
padx=3,
pady=3, sticky="we")
tk.Label(frame, bg=self.rbg,
text="Discretization type").grid(column=0,
row=8,
padx=3,
pady=3, sticky="w")
self.ra_rfg_dit_value = tk.StringVar(value="FBN")
self.ra_rfg_dit_value.set(self.ras_rfg_dit_value[oid].get())
w = tk.OptionMenu(frame, self.ra_rfg_dit_value, "FBN", "FBS")
w.config(indicatoron=False, compound='right', image=self.arr_img)
w.config(highlightthickness=0, highlightbackground="black")
w.grid(column=1,
row=8,
padx=3,
pady=3, sticky="we")
tk.Label(frame, bg=self.rbg,
text="Image quantization flag").grid(column=2, row=8, padx=(20, 3), pady=3, sticky="w")
self.ra_rfg_iqf_value = tk.StringVar(value="0")
self.ra_rfg_iqf_value.set(self.ras_rfg_iqf_value[oid].get())
w = tk.OptionMenu(frame, self.ra_rfg_iqf_value, "0", "1")
w.config(indicatoron=False, compound='right', image=self.arr_img)
w.config(highlightthickness=0, highlightbackground="black")
w.grid(column=3,
row=8,
padx=3,
pady=3, sticky="we")
tk.Label(frame, bg=self.rbg,
text="Bin size/width").grid(column=0, row=9, padx=3, pady=3, sticky="w")
self.ra_rgd_nhb_value = tk.StringVar(value="8")
self.ra_rgd_nhb_value.set(self.ras_rgd_nhb_value[oid].get())
ttk.Entry(frame, textvariable=self.ra_rgd_nhb_value, validate="all", justify="center",
validatecommand=(frame.register(_validate_c), "%P", 0, 128)).grid(column=1, row=9, padx=3, pady=3,
sticky="we")
tk.Label(frame, bg=self.rbg, text="Re-segmentation interval range").grid(column=2, row=9, padx=(20, 2), pady=3,
sticky="w")
tk.Label(frame, bg=self.rbg, text="[").grid(column=3, row=9, padx=(0, 0), pady=3, sticky="w")
self.ra_rgd_rir1_value = tk.StringVar(value=-3000)
self.ra_rgd_rir1_value.set(self.ras_rgd_rir1_value[oid].get())
ttk.Spinbox(frame, from_=-3000, to=0, textvariable=self.ra_rgd_rir1_value, validate="key", width=6,
validatecommand=(frame.register(_validate_int), "%P", -3000, 0), justify="center").grid(column=3, row=9,
padx=(0, 80),
pady=3,
sticky="e")
tk.Label(frame, bg=self.rbg, text=",").grid(column=3, row=9, padx=(70, 0), pady=3, sticky="w")
self.ra_rgd_rir2_value = tk.StringVar(value=3000)
self.ra_rgd_rir2_value.set(self.ras_rgd_rir2_value[oid].get())
ttk.Spinbox(frame, from_=0, to=3000, textvariable=self.ra_rgd_rir2_value, validate="key", width=6,
validatecommand=(frame.register(_validate_int), "%P", 0, 3000), justify="center").grid(column=3, row=9,
padx=(80, 0),
pady=3,
sticky="w")
tk.Label(frame, bg=self.rbg, text="]").grid(column=3, row=9, padx=(140, 0), pady=0, sticky="w")
tk.Label(frame, bg=self.rbg, text="Resampling (scaling) flag").grid(column=0, row=10, padx=3, pady=3, sticky="w")
self.ra_rfg_rf_value = tk.StringVar(value="1")
self.ra_rfg_rf_value.set(self.ras_rfg_rf_value[oid].get())
w = tk.OptionMenu(frame, self.ra_rfg_rf_value, "0", "1")
w.config(indicatoron=False, compound='right', image=self.arr_img)
w.config(highlightthickness=0, highlightbackground="black")
w.grid(column=1, row=10, padx=3, pady=3, sticky="we")
tk.Label(frame, bg=self.rbg, text="ROI partial volume threshold").grid(column=2, row=10, padx=(20, 3), pady=3,
sticky="w")
self.ra_rgd_roi_value = tk.StringVar(value=0.5)
self.ra_rgd_roi_value.set(self.ras_rgd_roi_value[oid].get())
ttk.Spinbox(frame, from_=0, to=1, increment=0.1, textvariable=self.ra_rgd_roi_value, validate="key",
validatecommand=(frame.register(_validate), "%P", 0, 1), justify="center").grid(column=3, row=10,
padx=3, pady=3,
sticky="we")
tk.Label(frame, bg=self.rbg, text="Image resampling interpolation type").grid(column=0, row=11, padx=3, pady=3,
sticky="w")
self.ra_rfg_irit_value = tk.StringVar(value="Nearest")
self.ra_rfg_irit_value.set(self.ras_rfg_irit_value[oid].get())
w = tk.OptionMenu(frame, self.ra_rfg_irit_value, "Nearest", "Linear", "Cubic")
w.config(indicatoron=False, compound='right', image=self.arr_img)
w.config(highlightthickness=0, highlightbackground="black")
w.grid(column=1, row=11, padx=3, pady=3, sticky="we")
tk.Label(frame, bg=self.rbg, text="Quantization type").grid(column=2, row=11, padx=(20, 3), pady=3, sticky="w")
self.ra_rfg_qt_value = tk.StringVar(value="Uniform")
self.ra_rfg_qt_value.set(self.ras_rfg_qt_value[oid].get())
w = tk.OptionMenu(frame, self.ra_rfg_qt_value, "Uniform")
w.config(indicatoron=False, compound='right', image=self.arr_img)
w.config(highlightthickness=0, highlightbackground="black")
w.grid(column=3, row=11, padx=3, pady=3, sticky="we")
tk.Label(frame, bg=self.rbg, text="ROI resampling interpolation type").grid(column=0, row=12, padx=3, pady=3,
sticky="w")
self.ra_rfg_roit_value = tk.StringVar(value="Nearest")
self.ra_rfg_roit_value.set(self.ras_rfg_roit_value[oid].get())
w = tk.OptionMenu(frame, self.ra_rfg_roit_value, "Nearest", "Linear", "Cubic")
w.config(indicatoron=False, compound='right', image=self.arr_img)
w.config(highlightthickness=0, highlightbackground="black")
w.grid(column=1, row=12, padx=3, pady=3, sticky="we")
tk.Label(frame, bg=self.rbg, text="Intensity volume histogram (IVH) type").grid(column=2, row=12, padx=(20, 3),
pady=3, sticky="w")
self.ra_rfg_ivht_value = tk.StringVar(value="1")
self.ra_rfg_ivht_value.set(self.ras_rfg_ivht_value[oid].get())
w = tk.OptionMenu(frame, self.ra_rfg_ivht_value, "0", "1", "2", "3")
w.config(indicatoron=False, compound='right', image=self.arr_img)
w.config(highlightthickness=0, highlightbackground="black")
w.grid(column=3, row=12, padx=3, pady=3, sticky="we")
tk.Label(frame, bg=self.rbg, text="3D isotropic voxel size flag (mm)").grid(column=0, row=13, padx=3, pady=3,
sticky="w")
self.ra_rgd_3ivs_value = tk.StringVar(value=6.00)
self.ra_rgd_3ivs_value.set(self.ras_rgd_3ivs_value[oid].get())
ttk.Spinbox(frame, from_=0, to=50, increment=1, textvariable=self.ra_rgd_3ivs_value, validate="key",
validatecommand=(frame.register(_validate), "%P", 0, 50), justify="center").grid(column=1, row=13,
padx=3, pady=3,
sticky="we")
tk.Label(frame, bg=self.rbg, text="IVH discretization type").grid(column=2, row=13, padx=(20, 3), pady=3,
sticky="w")
self.ra_rfg_idt_value = tk.StringVar(value="0")
self.ra_rfg_idt_value.set(self.ras_rfg_idt_value[oid].get())
w = tk.OptionMenu(frame, self.ra_rfg_idt_value, "0", "1")
w.config(indicatoron=False, compound='right', image=self.arr_img)
w.config(highlightthickness=0, highlightbackground="black")
w.grid(column=3, row=13, padx=3, pady=3, sticky="we")
tk.Label(frame, bg=self.rbg, text="2D isotropic voxel size flag (mm)").grid(column=0,
row=14,
padx=3,
pady=3, sticky="w")
self.ra_rgd_2ivs_value = tk.StringVar(value=1.00)
self.ra_rgd_2ivs_value.set(self.ras_rgd_2ivs_value[oid].get())
ttk.Spinbox(frame, from_=0, to=50, increment=1, textvariable=self.ra_rgd_2ivs_value, validate="key",
validatecommand=(frame.register(_validate), "%P", 0, 50), justify="center").grid(column=1,
row=14,
padx=3,
pady=3, sticky="we")
tk.Label(frame, bg=self.rbg,
text="IVH discretization binning option (number/width)").grid(column=2, row=14, padx=(20, 3), pady=3,
sticky="w")
self.ra_rgd_ivho_value = tk.StringVar(value=200.00)
self.ra_rgd_ivho_value.set(self.ras_rgd_ivho_value[oid].get())
ttk.Spinbox(frame, from_=0, to=1000, increment=1, textvariable=self.ra_rgd_ivho_value, validate="key",
validatecommand=(frame.register(_validate), "%P", 0, 1000), justify="center").grid(column=3,
row=14,
padx=3,
pady=3, sticky="we")
tk.Label(frame, bg=self.rbg,
text="Isotropic 2D voxels flag").grid(column=0,
row=15,
padx=3,
pady=3, sticky="w")
self.ra_rfg_i2vf_value = tk.StringVar(value="0")
self.ra_rfg_i2vf_value.set(self.ras_rfg_i2vf_value[oid].get())
w = tk.OptionMenu(frame, self.ra_rfg_i2vf_value, "0", "1")
w.config(indicatoron=False, compound='right', image=self.arr_img)
w.config(highlightthickness=0, highlightbackground="black")
w.grid(column=1,
row=15,
padx=3,
pady=3, sticky="we")
tk.Label(frame, bg=self.rbg,
text="Max number of ROIs per image").grid(column=2, row=15, padx=(20, 3), pady=3, sticky="w")
self.ra_rgd_mri_value = tk.StringVar(value="4")
self.ra_rgd_mri_value.set(self.ras_rgd_mri_value[oid].get())
ttk.Spinbox(frame, from_=0, to=1000000, textvariable=self.ra_rgd_mri_value, validate="key",
validatecommand=(frame.register(_validate_int), "%P", 0, 1000000), justify="center").grid(column=3,
row=15,
padx=3,
pady=3,
sticky="we")
tk.Label(frame, bg=self.rbg,
text="Round voxel intensity values flag").grid(column=0,
row=16,
padx=3,
pady=3, sticky="w")
self.ra_rfg_rviv_value = tk.StringVar(value="0")
self.ra_rfg_rviv_value.set(self.ras_rfg_rviv_value[oid].get())
w = tk.OptionMenu(frame, self.ra_rfg_rviv_value, "0", "1")
w.config(indicatoron=False, compound='right', image=self.arr_img)
w.config(highlightthickness=0, highlightbackground="black")
w.grid(column=1,
row=16,
padx=3,
pady=3, sticky="we")
tk.Label(frame, bg=self.rbg,
text="Combine multiple ROIs to one flag").grid(column=2, row=16, padx=(20, 3), pady=3, sticky="w")
self.ra_rfg_cmrf_value = tk.StringVar(value="0")
self.ra_rfg_cmrf_value.set(self.ras_rfg_cmrf_value[oid].get())
w = tk.OptionMenu(frame, self.ra_rfg_cmrf_value, "0", "1")
w.config(indicatoron=False, compound='right', image=self.arr_img)
w.config(highlightthickness=0, highlightbackground="black")
w.grid(column=3,
row=16,
padx=3,
pady=3, sticky="we")
tk.Label(frame, bg=self.rbg,
text="Range re-segmentation flag").grid(column=0,
row=17,
padx=3,
pady=3, sticky="w")
self.ra_rfg_rrf_value = tk.StringVar(value="0")
self.ra_rfg_rrf_value.set(self.ras_rfg_rrf_value[oid].get())
w = tk.OptionMenu(frame, self.ra_rfg_rrf_value, "0", "1")
w.config(indicatoron=False, compound='right', image=self.arr_img)
w.config(highlightthickness=0, highlightbackground="black")
w.grid(column=1,
row=17,
padx=3,
pady=3, sticky="we")
tk.Label(frame, text="Type of output data", bg=self.rbg).grid(column=2, row=17, padx=(20, 3), pady=3, sticky="w")
self.ra_rfg_tod_value = tk.StringVar(value="2")
self.ra_rfg_tod_value.set(self.ras_rfg_tod_value[oid].get())
w = tk.OptionMenu(frame, self.ra_rfg_tod_value, "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12")
w.config(indicatoron=False, compound='right', image=self.arr_img)
w.config(highlightthickness=0, highlightbackground="black")
w.grid(column=3,
row=17,
padx=3,
pady=3, sticky="we")
# last row
# self.close_photo = tk.PhotoImage(file="images/close.png")
# self.close_photo = self.close_photo.zoom(5)
# self.close_photo = self.close_photo.subsample(3)
def destroy():
self.set_radiomix_params(oid)
root.quit()
root.destroy()
main.none = True
def close():
main.quit()
main.destroy()
# root.quit()
# root.destroy()
main.protocol("WM_DELETE_WINDOW", close)
# root.protocol("WM_DELETE_WINDOW", destroy)
# ttk.Button(root, image=self.close_photo, command=destroy).grid(column=3, row=18, sticky="e", padx=40)
tk.Button(root, image=self.close_photo, bg=self.rbg, command=destroy, borderwidth=0).grid(column=1, row=18,
columnspan=5, padx=124,
sticky="e", pady=(0, 5))
# self.ok_photo = tk.PhotoImage(file="images/OK 25.png")
# self.ok_photo = self.ok_photo.zoom(3)
# self.ok_photo = self.ok_photo.subsample(2)
def okf():
for it in self.ra_rgd_nhb_value.get().split(","):
if float(it) < 0 or float(it) > 128:
messagebox.showerror(title="Parameter range",
message="please select 'Bin size/width' paramter in [0, 128] range.")
return
if float(self.ra_rgd_rir1_value.get()) < -3000 or float(self.ra_rgd_rir1_value.get()) > 0:
messagebox.showerror(title="Parameter range",
message="please select 'Re-segmentation interval range' paramter in [-3000, 3000] range.")
elif float(self.ra_rgd_rir2_value.get()) < 0 or float(self.ra_rgd_rir2_value.get()) > 3000:
messagebox.showerror(title="Parameter range",
message="please select 'Re-segmentation interval range' paramter in [-3000, 3000] range.")
elif float(self.ra_rgd_roi_value.get()) < 0 or float(self.ra_rgd_roi_value.get()) > 1:
messagebox.showerror(title="Parameter range",
message="please select 'ROI partial volume threshold' paramter in [0, 1] range.")
elif float(self.ra_rgd_3ivs_value.get()) < 0 or float(self.ra_rgd_3ivs_value.get()) > 50:
messagebox.showerror(title="Parameter range",
message="please select '3D isotropic voxel size flag(mm)' paramter in [0, 50] range.")
elif float(self.ra_rgd_2ivs_value.get()) < 0 or float(self.ra_rgd_2ivs_value.get()) > 50:
messagebox.showerror(title="Parameter range",
message="please select '2D isotropic voxel size flag(mm)' paramter in [0, 50] range.")
elif float(self.ra_rgd_ivho_value.get()) < 0 or float(self.ra_rgd_ivho_value.get()) > 1000:
messagebox.showerror(title="Parameter range",
message="please select 'IVH discretization binning option (number/width)' paramter in [0, 1000] range.")
elif float(self.ra_rgd_mri_value.get()) < 0 or float(self.ra_rgd_mri_value.get()) > 1000:
messagebox.showerror(title="Parameter range",
message="please select 'Max no. of ROIs per image' paramter in [0, 1000] range.")
else:
change = False
change = self.check_entry(self.ras_rfg_tod_value[oid], self.ra_rfg_tod_value, change)
change = self.check_entry(self.ras_rfg_rrf_value[oid], self.ra_rfg_rrf_value, change)
change = self.check_entry(self.ras_rfg_cmrf_value[oid], self.ra_rfg_cmrf_value, change)
change = self.check_entry(self.ras_rfg_rviv_value[oid], self.ra_rfg_rviv_value, change)
change = self.check_entry(self.ras_rgd_mri_value[oid], self.ra_rgd_mri_value, change)
change = self.check_entry(self.ras_rfg_i2vf_value[oid], self.ra_rfg_i2vf_value, change)
change = self.check_entry(self.ras_rgd_ivho_value[oid], self.ra_rgd_ivho_value, change)
change = self.check_entry(self.ras_rgd_2ivs_value[oid], self.ra_rgd_2ivs_value, change)
change = self.check_entry(self.ras_rfg_idt_value[oid], self.ra_rfg_idt_value, change)
change = self.check_entry(self.ras_rgd_3ivs_value[oid], self.ra_rgd_3ivs_value, change)
change = self.check_entry(self.ras_rfg_ivht_value[oid], self.ra_rfg_ivht_value, change)
change = self.check_entry(self.ras_rfg_roit_value[oid], self.ra_rfg_roit_value, change)
change = self.check_entry(self.ras_rfg_qt_value[oid], self.ra_rfg_qt_value, change)
change = self.check_entry(self.ras_rfg_irit_value[oid], self.ra_rfg_irit_value, change)
change = self.check_entry(self.ras_rgd_roi_value[oid], self.ra_rgd_roi_value, change)
change = self.check_entry(self.ras_rfg_rf_value[oid], self.ra_rfg_rf_value, change)
change = self.check_entry(self.ras_rgd_rir2_value[oid], self.ra_rgd_rir2_value, change)
change = self.check_entry(self.ras_rgd_rir1_value[oid], self.ra_rgd_rir1_value, change)
change = self.check_entry(self.ras_rgd_nhb_value[oid], self.ra_rgd_nhb_value, change)
change = self.check_entry(self.ras_rfg_iqf_value[oid], self.ra_rfg_iqf_value, change)
change = self.check_entry(self.ras_rfg_dit_value[oid], self.ra_rfg_dit_value, change)
change = self.check_entry(self.ras_rfg_iorf_value[oid], self.ra_rfg_iorf_value, change)
change = self.check_entry(self.ras_rfg_imt_value[oid], self.ra_rfg_imt_value, change)
change = self.check_entry(self.ras_file_dest_lbl[oid], self.ra_file_dest_lbl, change)
change = self.check_entry(self.ras_file_slc2_lbl[oid], self.ra_file_slc2_lbl, change)
change = self.check_entry(self.ras_file_slc_lbl[oid], self.ra_file_slc_lbl, change)
change = self.check_entry(self.ras_file_folder[oid], self.ra_file_folder, change)
if change:
self.set_object_state(oid, 'normal', 'hidden', 'hidden', 'hidden')
self.check_connection_remove(oid)
root.quit()
root.destroy()
# ttk.Button(root, image=self.ok_photo, command=okf).grid(column=3, row=18, sticky="e")
tk.Button(root, image=self.ok_img, bg=self.rbg, command=okf, borderwidth=0).grid(column=5, row=18, sticky="e",
padx=(0, 16), pady=(0, 5))
root.mainloop()
if main.none:
return None
if not (self.ra_file_slc_lbl.get().startswith("Select ") or self.ra_file_slc2_lbl.get().startswith(
"Select ") or self.ra_file_dest_lbl.get().startswith("Select ")):
return True
return False
class RoundedButton(tk.Canvas):
def __init__(self, parent, width, height, corner_radius, padding, color, bg, command=None, text=""):
tk.Canvas.__init__(self, parent, borderwidth=0,
relief="flat", highlightthickness=0, bg=bg)
self.command = command
rad = 2 * corner_radius
def shape():
self.create_polygon((padding, height - corner_radius - padding, padding, corner_radius + padding,
padding + corner_radius, padding, width - padding - corner_radius, padding,
width - padding, corner_radius + padding, width - padding,
height - corner_radius - padding, width - padding - corner_radius, height - padding,
padding + corner_radius, height - padding), fill=color, outline=color)
self.create_arc((padding, padding + rad, padding + rad, padding), start=90, extent=90, fill=color,
outline=color)
self.create_arc((width - padding - rad, padding, width - padding, padding + rad), start=0, extent=90,
fill=color, outline=color)
self.create_arc((width - padding, height - rad - padding, width - padding - rad, height - padding),
start=270, extent=90, fill=color, outline=color)
self.create_arc((padding, height - padding - rad, padding + rad, height - padding), start=180, extent=90,
fill=color, outline=color)
self.create_text(width / 2, height / 2, text=text)
id = shape()
(x0, y0, x1, y1) = self.bbox("all")
width = (x1 - x0)
height = (y1 - y0)
self.configure(width=width, height=height)
self.bind("<ButtonPress-1>", self._on_press)
self.bind("<ButtonRelease-1>", self._on_release)
def _on_press(self, event):
self.configure(relief="sunken")
def _on_release(self, event):
self.configure(relief="raised")
if self.command is not None:
self.command()
Galaxy/galaxy/tools/radiuma/radiomics.xml
+25
View File
@@ -0,0 +1,25 @@
<tool id="radiuma_radiomics" name="Radiomics Feature Extractor" version="1.0.0">
<description>Extract IBSI-compliant radiomics features using PySERA</description>
<command>
python3 $__tool_directory__/run_radiomics.py
--image $image
--mask $mask
--output $output.extra_files_path
--categories "$categories"
--dimensions "$dimensions"
--apply_preprocessing "$apply_preprocessing"
</command>
<inputs>
<param name="image" type="data" format="nii" label="Input Image"/>
<param name="mask" type="data" format="nii" label="Segmentation Mask"/>
<param name="categories" type="text" value="glcm, glrlm" label="Feature Categories"/>
<param name="dimensions" type="text" value="1st, 2_5d, 3d" label="Spatial Dimensions"/>
<param name="apply_preprocessing" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Apply Preprocessing"/>
</inputs>
<outputs>
<data name="output" format="csv" label="Extracted Radiomics Features" from_work_dir="radiomics_features.csv"/>
</outputs>
<help>
This tool extracts handcrafted radiomics features from medical images using the PySERA library.
</help>
</tool>
Galaxy/galaxy/tools/radiuma/run_classifiers.py
+21
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@@ -0,0 +1,21 @@
from pysera.classifier import Classifier
import argparse
import pandas as pd
parser = argparse.ArgumentParser()
parser.add_argument("--x_train", required=True)
parser.add_argument("--y_train", required=True)
parser.add_argument("--x_val", required=True)
parser.add_argument("--y_val", required=True)
parser.add_argument("--algorithm", choices=["LogisticRegression", "KNeighborsClassifier"], required=True)
parser.add_argument("--output", required=True)
args = parser.parse_args()
X_train = pd.read_csv(args.x_train)
y_train = pd.read_csv(args.y_train)
X_val = pd.read_csv(args.x_val)
y_val = pd.read_csv(args.y_val)
clf = Classifier(X_train, y_train, X_val, y_val)
result = clf.run(algorithm=args.algorithm)
pd.DataFrame(result).to_csv(args.output, index=False)
Galaxy/galaxy/tools/radiuma/run_preprocessing.py
+19
View File
@@ -0,0 +1,19 @@
from pysera.preprocessing import Preprocessor
import argparse
import pandas as pd
parser = argparse.ArgumentParser()
parser.add_argument("--input", required=True)
parser.add_argument("--method", choices=["resample", "shuffle"], required=True)
parser.add_argument("--output", required=True)
args = parser.parse_args()
df = pd.read_csv(args.input)
prep = Preprocessor(df)
if args.method == "resample":
result = prep.resample()
elif args.method == "shuffle":
result = prep.shuffle()
result.to_csv(args.output, index=False)
Galaxy/galaxy/tools/radiuma/run_radiomics.py
+34
View File
@@ -0,0 +1,34 @@
# run_radiomics.py
import pysera
import argparse
import os
parser = argparse.ArgumentParser()
parser.add_argument("--image", required=True)
parser.add_argument("--mask", required=True)
parser.add_argument("--output", required=True)
parser.add_argument("--categories", default="glcm, glrlm")
parser.add_argument("--dimensions", default="1st, 2_5d, 3d")
parser.add_argument("--apply_preprocessing", default="True")
args = parser.parse_args()
# اطمینان از وجود مسیر خروجی
os.makedirs(args.output, exist_ok=True)
# اجرای PySERA
result = pysera.process_batch(
image_input=args.image,
mask_input=args.mask,
output_path=args.output,
categories=args.categories,
dimensions=args.dimensions,
apply_preprocessing=args.apply_preprocessing == "True"
)
# ذخیره خروجی ویژگی‌ها به CSV
if result["success"]:
features = result["features_extracted"]
features.to_csv(os.path.join(args.output, "radiomics_features.csv"), index=False)
else:
print("Error:", result.get("error", "Unknown error"))
Galaxy/pysera/__init__.py
+3
View File
@@ -0,0 +1,3 @@
from .classifiers import Classifiers
from .preprocessor import Preprocessor
from .radiomics_extractor import RadiomicsExtractor
Galaxy/pysera/classifiers.py
View File
Galaxy/pysera/preprocessor.py
+12
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@@ -0,0 +1,12 @@
import pandas as pd
from sklearn.utils import resample, shuffle
class Preprocessor:
def __init__(self, df: pd.DataFrame):
self.df = df
def resample(self, replace=False):
return resample(self.df, replace=replace)
def shuffle(self):
return shuffle(self.df)
Galaxy/pysera/radiomics_extractor.py
View File
Galaxy/requirements.txt
+90
View File
@@ -0,0 +1,90 @@
astroid==4.0.1
certifi==2025.10.5
charset-normalizer==3.4.4
cleo==2.1.0
colorama==0.4.6
connected-components-3d==3.26.0
contourpy==1.3.3
crashtest==0.4.1
cycler==0.12.1
dataclasses==0.6
dcmrtstruct2nii==5
dill==0.4.0
distlib==0.4.0
docx==0.2.4
et_xmlfile==2.0.0
filelock==3.20.0
fonttools==4.60.1
fpdf==1.7.2
fsspec==2025.9.0
idna==3.11
imageio==2.37.0
importlib_resources==6.5.2
iniconfig==2.3.0
isort==7.0.0
itk==5.4.4.post1
itk-core==5.4.4.post1
itk-filtering==5.4.4.post1
itk-io==5.4.4.post1
itk-numerics==5.4.4.post1
itk-registration==5.4.4.post1
itk-segmentation==5.4.4.post1
Jinja2==3.1.6
joblib==1.5.2
kiwisolver==1.4.9
kmodes==0.12.2
lazy_loader==0.4
lxml==6.0.2
MarkupSafe==3.0.3
matplotlib==3.10.7
mccabe==0.7.0
mpmath==1.3.0
networkx==3.5
nibabel==5.3.2
numpy==2.2.6
opencv-python==4.12.0.88
openpyxl==3.1.5
packaging==25.0
pandas==2.3.3
pillow==12.0.0
platformdirs==4.5.0
pluggy==1.6.0
psutil==7.1.2
psycopg2-binary==2.9.11
pyaml==25.7.0
pydicom==3.0.1
Pygments==2.19.2
pylint==4.0.1
pynrrd==1.1.3
pyparsing==3.2.5
pysera==2.1.2
pytest==8.4.2
python-dateutil==2.9.0.post0
python-docx==1.2.0
pytz==2025.2
PyWavelets==1.9.0
PyYAML==6.0.3
RapidFuzz==3.14.1
ReliefF==0.1.2
reportlab==4.4.4
requests==2.32.5
rt-utils==1.2.7
scikit-image==0.25.2
scikit-learn==1.7.2
scikit-optimize==0.10.2
scipy==1.16.3
six==1.17.0
sklearn-relief==1.0.0b2
sympy==1.14.0
termcolor==3.2.0
threadpoolctl==3.6.0
tifffile==2025.10.16
tomlkit==0.13.3
torch==2.8.0
torchaudio==2.8.0
torchvision==0.23.0
typing_extensions==4.15.0
tzdata==2025.2
uml-class-diagram-generator==0.1
urllib3==2.5.0
virtualenv==20.35.3