Search Results for author: Richard K. G. Do

Found 5 papers, 3 papers with code

Towards Optimal Patch Size in Vision Transformers for Tumor Segmentation

1 code implementation31 Aug 2023 Ramtin Mojtahedi, Mohammad Hamghalam, Richard K. G. Do, Amber L. Simpson

Although transformers can capture long-range features, their segmentation performance decreases with various tumor sizes due to the model sensitivity to the input patch size.

Segmentation Transfer Learning +1

Attention-based CT Scan Interpolation for Lesion Segmentation of Colorectal Liver Metastases

no code implementations30 Aug 2023 Mohammad Hamghalam, Richard K. G. Do, Amber L. Simpson

Small liver lesions common to colorectal liver metastases (CRLMs) are challenging for convolutional neural network (CNN) segmentation models, especially when we have a wide range of slice thicknesses in the computed tomography (CT) scans.

Computed Tomography (CT) Lesion Segmentation +1

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