COMP3710 Project 3: Improved 2D U-Net for HipMRI Prostate Segmentation#64

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prabhjotsingh1313 wants to merge 34 commits intoshakes76:mainfrom

prabhjotsingh1313:topic-recognition

Commits on Sep 21, 2025

Added recognition branch for tasks
shakes76
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Commits on Oct 29, 2025

Initial project scaffold for HipMRI prostate segmentation
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Add inital dataset with necessary imports and implemented build_pairs()
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Add label discovery function to scan segmentation files and extract unique label IDs from training set
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Implemented PyTorch dataset for paired MRI/seg nifti files and added z-score normalisation and one-hot encoding with risizing of 256x256
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added get_data_loaders for building train/val/test splits and label discovery
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Add dataloaders for train, validation, and test splits with batching, shuffling and metadata return
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add center_crop function for spatial alignment in Unet
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Add conv_block module with dual conv layers, batch norm and ReLU
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Add Down module for 2x downsampling using max pooling with a convolutional block to reduce spatial size and increase feature depth in the improved Unet
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Implemented Up block for Unet upsampling wih skip connections
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Added ImprovedUNet2D with deeper layers and dilated bottleneck for segmentation
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Implemented dice_per_channel() to compute dice score and implemented dice_loss() for model training
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Added training and validation script for unet2D using dice loss in run_one_epoch()
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Implemented evaluate_dice() function for per channel dice evaluation, uses no_grad() and eval mode
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Implemented plot_training_curves to plot and save training/validation loss curves
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Initialise README
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Refactored improved Unet into recognition/improved2DUnet module
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Remove duplicate scripts from recognition root after module refactor
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Added main training script with full pipeline for improved2DUnet. Included arguement parsing, data loading, training/validation loop with dice loss, checkpoint saving and loss plotting
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Added utility for creating fixed colourmap for multi-class segmentation masks
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Added batch visualisation function for MRI segmentation and prostate overlay
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Added full inference pipeline including load checkpoint, run prediction, compute dice per channel and overlay prostate mask
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Implemented inference script with argument parsing for data, checkpoint, device, and output visualisation
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Commits on Oct 30, 2025