Ablation study results on ISIC2018.

<div><p>Although recent advances in CNNs and Transformers have significantly improved medical image segmentation, these models often struggle to balance segmentation accuracy, inference speed, and architectural simplicity. Lightweight MLP-based methods have emerged as a promising alterna...

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Bibliographic Details
Main Author:	Şafak Kılıç (22227019) (author)
Published:	2025
Subjects:	Biophysics Medicine Biotechnology Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified thereby enhancing applicability suboptimal boundary localization preserving low latency models often struggle grained spatial context enhancing feature selectivity dataset generalization capability challenging task requiring skin lesion segmentation convolution hybrid network achieving dice scores minimal architectural complexity time clinical settings paper introduces focusgate convolutional feature extractors balance segmentation accuracy based hybrid architectures attention guided mlp clinical settings polyp segmentation mlp architectures hybrid design hybrid architecture dice coefficient based modules based methods attention gate architectural simplicity architectural component unet ++, results highlight promising alternative lightweight mlp inference speed frequently lack evaluate focusgate design aims dermatoscopic images computational efficiency capture fine approach leverages
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Ablation study results on ISIC2018.

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