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MRI_image_classification

Keras implementation of our normalized spatial attention paper "AN L2-NORMALIZED SPATIAL ATTENTION NETWORK FOR ACCURATE AND FAST CLASSIFICATION OF BRAIN TUMORS IN 2D T1-WEIGHTED CE-MRI IMAGES" [1] accepted at ICIP 2023

Cheng et al. dataset [2] can be downloaded from: https://figshare.com/articles/brain_tumor_dataset/1512427

Tested in Python 3.9.12, Tensorflow 2.9.1 and Keras 2.9.0

References:

[1] Grace Billingsley, Julia Dietlmeier, Vivek Narayanaswamy, Andreas Spanias, Noel E. O’Connor "AN L2-NORMALIZED SPATIAL ATTENTION NETWORK FOR ACCURATE AND FAST CLASSIFICATION OF BRAIN TUMORS IN 2D T1-WEIGHTED CE-MRI IMAGES", International Conference on Image Processing (ICIP 2023), Kuala Lumpur, Malaysia, October 8-11, 2023

[2] Jun Cheng, Wei Huang, Shuangliang Cao, Ru Yang, Wei Yang, Zhaoqiang Yun, Zhijian Wang, Qianjin Feng, ”Enhanced Performance of Brain Tumor Classification via Tumor Region Augmentation and Partition”, PLoS ONE 10(10): e0140381, 2015

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