Mind the Gap: Promoting Missing Modality Brain Tumor Segmentation with Alignment

Brain tumor segmentation is often based on multiple magnetic resonance imaging (MRI). However, in clinical practice, certain modalities of MRI may be missing, which presents an even more difficult scenario. To cope with this challenge, knowledge distillation has emerged as one promising strategy. However, recent efforts typically overlook the modality gaps and thus fail to learn invariant feature representations across different modalities. Such drawback consequently leads to limited performance for both teachers and students. To ameliorate these problems, in this paper, we propose a novel paradigm that aligns latent features of involved modalities to a well-defined distribution anchor. As a major contribution, we prove that our novel training paradigm ensures a tight evidence lower bound, thus theoretically certifying its effectiveness. Extensive experiments on different backbones validate that the proposed paradigm can enable invariant feature representations and produce a teacher with narrowed modality gaps. This further offers superior guidance for missing modality students, achieving an average improvement of 1.75 on dice score.

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Published
2024-12-03
DOI
https://doi.org/10.1109/bibm62325.2024.10822387
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.00

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article

Mind the Gap: Promoting Missing Modality Brain Tumor Segmentation with Alignment

Haochuan Jiang, Kaizhu Huang, Xi Yang, Zhaorui Tan et al.
Brain Tumor Detection and Classification
article

Mind the Gap: Promoting Missing Modality Brain Tumor Segmentation with Alignment

Haochuan Jiang, Kaizhu Huang, Xi Yang, Zhaorui Tan, Tianyi Liu
article en

Abstract

Brain tumor segmentation is often based on multiple magnetic resonance imaging (MRI). However, in clinical practice, certain modalities of MRI may be missing, which presents an even more difficult scenario. To cope with this challenge, knowledge distillation has emerged as one promising strategy. However, recent efforts typically overlook the modality gaps and thus fail to learn invariant feature representations across different modalities. Such drawback consequently leads to limited performance for both teachers and students. To ameliorate these problems, in this paper, we propose a novel paradigm that aligns latent features of involved modalities to a well-defined distribution anchor. As a major contribution, we prove that our novel training paradigm ensures a tight evidence lower bound, thus theoretically certifying its effectiveness. Extensive experiments on different backbones validate that the proposed paradigm can enable invariant feature representations and produce a teacher with narrowed modality gaps. This further offers superior guidance for missing modality students, achieving an average improvement of 1.75 on dice score.

Duke Kunshan University (CN), Xi’an Jiaotong-Liverpool University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Jiangsu Province
Reduced inequalities
Openalex Percentile: Top 70%
Brain Tumor Detection and Classification
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Mind the Gap: Promoting Missing Modality Brain Tumor Segmentation with Alignment — Haochuan Jiang, Kaizhu Huang, et al. · (2024) | TGRS Research Map | TGRS