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Partition-A-Medical-Image: Extracting Multiple Representative Sub-regions for Few-shot Medical Image Segmentation

Lookup NU author(s): Dr Shidong WangORCiD, Dr Tong XinORCiD

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Abstract

IEEEFew-shot Medical Image Segmentation (FSMIS) is a more promising solution for medical image segmentation tasks where high-quality annotations are naturally scarce. However, current mainstream methods primarily focus on extracting holistic representations from support images with large intra-class variations in appearance and background, and encounter difficulties in adapting to query images. In this work, we present an approach to extract multiple representative sub-regions from a given support medical image, enabling fine-grained selection over the generated image regions. Specifically, the foreground of the support image is decomposed into distinct regions, which are subsequently used to derive region-level representations via a designed Regional Prototypical Learning (RPL) module. We then introduce a novel Prototypical Representation Debiasing (PRD) module based on a two-way elimination mechanism which suppresses the disturbance of regional representations by a self-support, Multi-direction Self-debiasing (MS) block, and a support-query, Interactive Debiasing (ID) block. Finally, an Assembled Prediction (AP) module is devised to balance and integrate predictions of multiple prototypical representations learned using stacked PRD modules. Results obtained through extensive experiments on three publicly accessible medical imaging datasets demonstrate consistent improvements over the leading FSMIS methods. The source code is available at https://github.com/YazhouZhu19/PAMI.


Publication metadata

Author(s): Zhu Y, Wang S, Xin T, Zhang Z, Zhang H

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Instrumentation and Measurement

Year: 2024

Volume: 73

Online publication date: 26/03/2024

Acceptance date: 02/04/2018

ISSN (print): 0018-9456

ISSN (electronic): 1557-9662

Publisher: Institute of Electrical and Electronics Engineers Inc.

URL: https://doi.org/10.1109/TIM.2024.3381715

DOI: 10.1109/TIM.2024.3381715


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