Halo i want to combine 2d slices oct skin images into 3d, after that i want to make an automatic detection volume of epidermis and stratum corneum

i already combine like this

% Initialize variables

rows = []; columns = [];

% Loop through each slice

for k = 1:100

fileName = sprintf('_%d.txt', k);

% Read the text file

sliceImage = dlmread(fileName);

% Check the size of the first slice to initialize the 3D array

if isempty(rows) || isempty(columns)

[rows, columns] = size(sliceImage);

image3d = zeros(rows, columns, 8, 'uint8'); % Initialize 3D array

end

% Convert to uint8

sliceImage = uint8(sliceImage);

% Put this slice into plane k of the 3D image

image3d(:, :, k) = sliceImage;

end

Answer 1

[praguna manvi]

Hi @Gilang,

The implementation for converting 2D slices to 3D above looks correct. However, you could change the initialization of “image3d” to:

image3d = zeros(rows, columns, 100, 'uint8'); % Initialize 3D array with correct size

Refer to this link for different methods such as using "cat" to achieve the same functionality : https://www.mathworks.com/matlabcentral/answers/154714-how-can-i-convert-2d-images-to-a-3d-image

To visualize and process Regions of Interest (ROI) and skin layer regions in images using MATLAB refer to this link:

https://www.mathworks.com/help/images/roi-based-processing.html

To perform automatic detection of volumes of specific types, you can adopt deep learning methods like "unet-3d," which is a "CNN" architecture designed for image segmentation with a symmetric encoder-decoder structure and skip connections, more information here :

https://www.mathworks.com/matlabcentral/answers/1576008-i-want-to-create-an-automated-fracture-detection-using-machine-learning-from-ct-3d-volume-what-is-t