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import streamlit as st | |
import mahotas as mh | |
import pandas as pd | |
import plotly.express as px | |
import urllib.request | |
from skimage import io | |
# Define a list of medical conditions | |
conditions = [ | |
{"name": "Depression", "test_for": "Patient Health Questionnaire-9 (PHQ-9)"}, | |
{"name": "Anxiety", "test_for": "Generalized Anxiety Disorder-7 (GAD-7)"}, | |
{"name": "Diabetes", "test_for": "Hemoglobin A1C test"}, | |
{"name": "Hypertension", "test_for": "Blood pressure measurement"}, | |
{"name": "Asthma", "test_for": "Pulmonary function test"}, | |
{"name": "Cancer", "test_for": "Biopsy or imaging tests (e.g., CT scan, MRI)"}, | |
{"name": "Arthritis", "test_for": "X-ray, MRI, or ultrasound"}, | |
{"name": "Heart disease", "test_for": "Electrocardiogram (ECG)"}, | |
{"name": "Obesity", "test_for": "Body mass index (BMI)"}, | |
{"name": "Substance use disorder", "test_for": "Substance Abuse Subtle Screening Inventory (SASSI)"} | |
] | |
# Define a function to process images using Mahotas | |
def process_image(image): | |
# Convert the image to grayscale | |
grayscale_image = mh.colors.rgb2gray(image) | |
# Apply a Gaussian filter to the image to reduce noise | |
filtered_image = mh.gaussian_filter(grayscale_image, 4) | |
# Threshold the image to create a binary image | |
binary_image = filtered_image > mh.otsu(filtered_image) | |
# Compute the connected components in the binary image | |
labels, num_labels = mh.label(binary_image) | |
# Compute the size of each connected component | |
sizes = mh.labeled.labeled_size(labels) | |
# Sort the sizes in descending order | |
sorted_sizes = sorted(sizes, reverse=True) | |
# Return the top 10 sizes | |
return sorted_sizes[:10] | |
# Define the Streamlit app | |
def app(): | |
# Add a title to the app | |
st.title("Mahotas Demo") | |
# Add a sidebar to the app | |
st.sidebar.title("Medical Conditions") | |
selected_condition = st.sidebar.selectbox("Select a condition", [c["name"] for c in conditions]) | |
# Get the selected condition | |
condition = next(c for c in conditions if c["name"] == selected_condition) | |
# Display the selected condition | |
st.header(condition["name"]) | |
st.write("Test for:", condition["test_for"]) | |
# Load an example medical image | |
if selected_condition == "Depression": | |
image_url = "https://i.imgur.com/kPQoD8C.jpg" | |
elif selected_condition == "Anxiety": | |
image_url = "https://i.imgur.com/ZWyKjJN.jpg" | |
elif selected_condition == "Diabetes": | |
image_url = "https://i.imgur.com/1gOEMO5.jpg" | |
elif selected_condition == "Hypertension": | |
image_url = "https://i.imgur.com/BoSUwio.jpg" | |
elif selected_condition == "Asthma": | |
image_url = "https://i.imgur.com/BLKjzJF.jpg" | |
elif selected_condition == "Cancer": | |
image_url = "https://i.imgur.com/nq3vV8.jpg" | |
elif selected_condition == "Arthritis": | |
image_url = "https://i.imgur.com/ffzd6Fo.jpg" | |
elif selected_condition == "Heart disease": | |
image_url = "https://i.imgur.com/1I7axhd.jpg" | |
elif selected_condition == "Obesity": | |
image_url = "https://i.imgur.com/nZ1EjJr.jpg" | |
else: | |
image_url = "https://i.imgur.com/RUBZOWF.jpg" | |
image = io.imread(image_url) | |
# Process the image using Mahotas | |
sizes = process_image(image) | |
# Display the top 10 connected component sizes | |
df = pd.DataFrame({"Size": sizes}) | |
st.write(df) | |
# Create a sunburst chart using Plotly | |
fig = px.sunburst( | |
df, | |
path=["Size"], | |
values="Size", | |
color="Size", | |
color_continuous_scale="blues" | |
) | |
st.plotly_chart(fig) | |
st.markdown(""" | |
# Alternate Image Links Per Condition: | |
Depression: https://www.pexels.com/photo/woman-sitting-on-grass-field-while-holding-her-head-7127866/ | |
Anxiety: https://www.pexels.com/photo/woman-sitting-on-rock-and-looking-at-the-ocean-7119798/ | |
Diabetes: https://www.pexels.com/photo/man-taking-blood-sugar-test-4050305/ | |
Hypertension: https://www.pexels.com/photo/woman-measuring-blood-pressure-with-sphygmomanometer-5691686/ | |
Asthma: https://www.pexels.com/photo/woman-having-asthma-attack-in-park-7127511/ | |
Cancer: https://www.pexels.com/photo/close-up-of-pink-ribbon-on-cancer-awareness-banner-4219366/ | |
Arthritis: https://www.pexels.com/photo/man-with-back-pain-lying-on-bed-4050323/ | |
Heart disease: https://www.pexels.com/photo/woman-touching-chest-during-chest-pain-7127487/ | |
Obesity: https://www.pexels.com/photo/woman-in-black-pants-lying-on-bed-7127516/ | |
""") |