Mustafa Ipekbayrak - Full-Stack Developer and Cyber Security Analyst

Mammography Cancer Detection Application

import numpy as np
from skimage import io
from skimage.color import rgb2gray
from skimage.measure import regionprops
import matplotlib.pyplot as plt
from skimage.transform import rotate
import base64
from io import BytesIO

# Assuming 'selected_image_base64' is a base64 encoded string
image_data = base64.b64decode(selected_image_base64)
image_data = BytesIO(image_data)

# Reading the image from bytes data
originalIm = io.imread(image_data)        

# Convert the image to binary
bw = (originalIm > (255 / 2)).astype('uint8')

# Get the region properties
s = regionprops(bw)

phi = np.linspace(0, 2 * np.pi, 50)
cosphi = np.cos(phi)
sinphi = np.sin(phi)

imarray = []
plotarrayX = []
plotarrayY = []

textarray = []

xbarbarray = []
ybaraarray = []

aa = []
ba = []

# Loop through each region in the region properties object
for region in s:
    y0, x0 = region.centroid

    a = region.major_axis_length / 2.0
    b = region.minor_axis_length / 2.0

    orientation = region.orientation

    # Rotation matrix
    R = np.array([[np.cos(orientation), -np.sin(orientation)], 
                  [np.sin(orientation), np.cos(orientation)]])
    
    # Ellipse coordinates
    xy = np.array([a * cosphi, b * sinphi])
    xy = np.dot(R, xy)
    x = xy[0, :] + x0
    y = xy[1, :] + y0
    
    # Condition to proceed with the plotting and mask creation
    if region.minor_axis_length > 5 and region.major_axis_length > 60:
        YourText = f'Orientation: {region.orientation}\nArea: {a*b*np.pi}'
        plotarrayX.append(x)
        plotarrayY.append(y)
        textarray.append(YourText)
        xbarbarray.append(x0)
        ybaraarray.append(y0)
        aa.append(a)
        ba.append(b)

        # Create an ellipse mask and rotate it
        rr, cc = np.meshgrid(np.arange(originalIm.shape[1]), np.arange(originalIm.shape[0]))
        ellipse_mask = ((cc - y0)**2 / b**2 + (rr - x0)**2 / a**2) <= 1
        RotateEllipse = rotate(ellipse_mask, np.degrees(orientation), center=(x0, y0), mode='constant', cval=0)
        
        # Get the part of the original image where the ellipse is found
        A_cropped = originalIm * RotateEllipse.astype('uint8')
        imarray.append(A_cropped)

# Create the new image
new_image = ~bw
new_image = (new_image * 255).astype('uint8')

# Loop through each array in imarray and add it to new_image
for image in imarray:
    new_image = np.maximum(new_image, image)

# Plotting
plt.imshow(new_image, cmap='gray')

for i, x in enumerate(plotarrayX):
    plt.plot(x, plotarrayY[i], 'r', linewidth=2)
    plt.text(xbarbarray[i] - 150, ybaraarray[i], textarray[i], color=[0, 0, 1], fontsize=12)

plt.show()
plt.savefig('my_plot.png')
# Save the resulting image to a file
output_image_path = "/tmp/result_image.png"
io.imsave(output_image_path, new_image)

# Convert the file path to a data URL so it can be displayed in the web browser
import base64

with open('my_plot.png', "rb") as f:
    result_image_data_url = "data:image/png;base64," + base64.b64encode(f.read()).decode("utf-8")
    
# Set the data URL as the value of the 'result_image_path' variable
result_image_path = result_image_data_url
View the source code on GitHub
Output:
You can execute any Python code. Just select an image and click the button.
Result: