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arXiv · 2303.14998

Multi-view Cross-Modality MR Image Translation for Vestibular Schwannoma and Cochlea Segmentation

Bogyeong Kang·Hyeonyeong Nam·Ji-Wung Han·Keun-Soo Heo·Tae-Eui Kam
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Abstract

In this work, we propose a multi-view image translation framework, which can translate contrast-enhanced T1 (ceT1) MR imaging to high-resolution T2 (hrT2) MR imaging for unsupervised vestibular schwannoma and cochlea segmentation. We adopt two image translation models in parallel that use a pixel-level consistent constraint and a patch-level contrastive constraint, respectively. Thereby, we can augment pseudo-hrT2 images reflecting different perspectives, which eventually lead to a high-performing segmentation model. Our experimental results on the CrossMoDA challenge show that the proposed method achieved enhanced performance on the vestibular schwannoma and cochlea segmentation.

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Bogyeong Kang, Hyeonyeong Nam, Ji-Wung Han, Keun-Soo Heo, Tae-Eui Kam. 2023-03-27. Multi-view Cross-Modality MR Image Translation for Vestibular Schwannoma and Cochlea Segmentation. https://arxiv.org/abs/2303.14998

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