/MedVQA_FITS

TYPE-AWARE MEDICAL VISUAL QUESTION ANSWERING, ICASSP 2022

Primary LanguagePython

FITS_Model

This repository contains the core code of "TYPE-AWARE MEDICAL VISUAL QUESTION ANSWERING" in ICASSP 2022.

Setting

Image Pretrained model

We crawled 727 radiology medical images from PEIR Digital Library and pretrained these images on CotNet152 as visual feature extract model.

Language Pretrained model

We used BioM-ELECTRA-Base-SQuAD2 from Biom-transformers as text feature extract model.

Citation

@inproceedings{DBLP:conf/icassp/ZhangTLWZ22,
  author    = {Anda Zhang and
               Wei Tao and
               Ziyan Li and
               Haofen Wang and
               Wenqiang Zhang},
  title     = {Type-Aware Medical Visual Question Answering},
  booktitle = {{IEEE} International Conference on Acoustics, Speech and Signal Processing,
               {ICASSP} 2022, Virtual and Singapore, 23-27 May 2022},
  pages     = {4838--4842},
  publisher = {{IEEE}},
  year      = {2022},
  url       = {https://doi.org/10.1109/ICASSP43922.2022.9747087},
  doi       = {10.1109/ICASSP43922.2022.9747087},
  timestamp = {Fri, 24 Jun 2022 12:17:37 +0200},
  biburl    = {https://dblp.org/rec/conf/icassp/ZhangTLWZ22.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}