3D Convolutional Neural Networks for Brain Tumor Segmentation: A\n Comparison of Multi-resolution Architectures

2017/05/23 by Adrià Casamitjana, Santi Puch, Casamitjana, Adrià +5
Computer Science · Neuroscience · #Advanced Neural Network Applications #Brain Tumor Detection and Classification #FOS: Computer and information sciences #Machine Learning (stat.ML) #Medical Image Segmentation Techniques

paper · pdf · doi:10.48550/arxiv.1705.08236

openalex publication_date 2017/05/23 · openalex created_date 2022/10/06 · openalex updated_date 2026/07/28

Abstract

This paper analyzes the use of 3D Convolutional Neural Networks for brain\ntumor segmentation in MR images. We address the problem using three different\narchitectures that combine fine and coarse features to obtain the final\nsegmentation. We compare three different networks that use multi-resolution\nfeatures in terms of both design and performance and we show that they improve\ntheir single-resolution counterparts.\n

Citations

• The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

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