@inproceedings{b2a1b3822aa74ac7a87362eb06c2e479,
title = "Holistic brain tumor screening and classification based on densenet and recurrent neural network",
abstract = "We present a holistic brain tumor screening and classification method for detecting and distinguishing multiple types of brain tumors on MR images. The challenges arise from the significant variations of location, shape, size, and contrast of these tumors. The proposed algorithms start with feature extraction from axial slices using dense convolutional neural networks; the obtained sequential features of multiple frames are then fed into a recurrent neural network for classification. Different from most other brain tumor classification algorithms, our framework is free from manual or automatic region of interests segmentation. The results reported on a public dataset and a population of 422 proprietary MRI scans diagnosed as normal, gliomas, meningiomas and metastatic brain tumors demonstrate the effectiveness and efficiency of our method.",
author = "Yufan Zhou and Zheshuo Li and Hong Zhu and Changyou Chen and Mingchen Gao and Kai Xu and Jinhui Xu",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 4th International MICCAI Brainlesion Workshop, BrainLes 2018 held in conjunction with the Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2018 ; Conference date: 16-09-2018 Through 20-09-2018",
year = "2019",
doi = "10.1007/978-3-030-11723-8\_21",
language = "English",
isbn = "9783030117221",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "208--217",
editor = "\{van Walsum\}, Theo and Mauricio Reyes and Alessandro Crimi and Spyridon Bakas and Farahani Keyvan and Hugo Kuijf",
booktitle = "Brainlesion",
address = "Germany",
}