Multimodal brain tumor classification

09/03/2020

∙

Cancer is a complex disease that provides various types of information depending on the scale of observation. While most tumor diagnostics are performed by observing histopathological slides, radiology images should yield additional knowledge towards the efficacy of cancer diagnostics. This work investigates a deep learning method combining whole slide images and magnetic resonance images to classify tumors. Experiments are prospectively conducted on the 2020 Computational Precision Medicine challenge, in a 3-classes unbalanced classification task. We report cross-validation (resp. validation) balanced-accuracy, kappa and f1 of 0.913, 0.897 and 0.951 (resp. 0.91, 0.90 and 0.94). The complete code of the method is open-source at XXXX. Those include histopathological data pre-processing, and can therefore be used off-the-shelf for other histopathological and/or radiological classification.

READ FULL TEXT

Multimodal brain tumor classification

Neural Gas Network Image Features and Segmentation for Brain Tumor Detection Using Magnetic Resonance Imaging Data

Brain Tumors Classification for MR images based on Attention Guided Deep Learning Model

Detection and Classification of Brain tumors Using Deep Convolutional Neural Networks

Brain Tumor Detection and Classification with Feed Forward Back-Prop Neural Network

Brain Tumor Segmentation by Cascaded Deep Neural Networks Using Multiple Image Scales

Triplet Contrastive Learning for Brain Tumor Classification

Noise-reducing attention cross fusion learning transformer for histological image classification of osteosarcoma

Multimodal brain tumor classification

Related Research

Neural Gas Network Image Features and Segmentation for Brain Tumor Detection Using Magnetic Resonance Imaging Data

Brain Tumors Classification for MR images based on Attention Guided Deep Learning Model

Detection and Classification of Brain tumors Using Deep Convolutional Neural Networks

Brain Tumor Detection and Classification with Feed Forward Back-Prop Neural Network

Brain Tumor Segmentation by Cascaded Deep Neural Networks Using Multiple Image Scales

Triplet Contrastive Learning for Brain Tumor Classification

Noise-reducing attention cross fusion learning transformer for histological image classification of osteosarcoma