2020
DOI: 10.48550/arxiv.2010.10563
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A Survey on Deep Learning and Explainability for Automatic Report Generation from Medical Images

Abstract: Every year physicians face an increasing demand of image-based diagnosis from patients, a problem that can be addressed with recent artificial intelligence methods. In this context, we survey works in the area of automatic report generation from medical images, with emphasis on methods using deep neural networks, with respect to: (1) Datasets, (2) Architecture Design, (3) Explainability and (4) Evaluation Metrics. Our survey identifies interesting developments, but also remaining challenges. Among them, the cu… Show more

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Cited by 2 publications
(3 citation statements)
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References 86 publications
(406 reference statements)
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“…In contrast to previous sections that discuss applications of ViTs, this section focuses on transformers as powerful language models. It is also pertinent to note that even though multiple surveys exist covering the applications of deep learning in clinical report generation [335]- [338], to the best of our knowledge, none of these have covered the applications of transformer models in the area despite having transformers' phenomenal impact since their inception back in 2017. In this regard, we hope this section will serve as a valuable resource to the research community.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…In contrast to previous sections that discuss applications of ViTs, this section focuses on transformers as powerful language models. It is also pertinent to note that even though multiple surveys exist covering the applications of deep learning in clinical report generation [335]- [338], to the best of our knowledge, none of these have covered the applications of transformer models in the area despite having transformers' phenomenal impact since their inception back in 2017. In this regard, we hope this section will serve as a valuable resource to the research community.…”
Section: Discussionmentioning
confidence: 99%
“…Recently, immense progress has been made to automatically generate clinical reports from medical images using deep learning [335]- [338]. This automatic report generation process can help clinicians in accurate decision-making.…”
Section: Clinical Report Generationmentioning
confidence: 99%
“…A number of studies have found an intimate connection between explainability and the safety of human life in security-critical areas, e.g., in medicine [9,17,2] or autonomous driving [25,8]. In the medical domain, decisions made by blackbox models are unreliable and thus unacceptable [28].…”
Section: Introductionmentioning
confidence: 99%