43 citations · 55 across the 7 of their papers we have counts for
7 papers
Rep-GLS: Report-Guided Generalized Label Smoothing for Robust Disease Detection
Kunyu Zhang, Fukang Ge, Binyang Wang +5
Unlike nature image classification where groundtruth label is explicit and of no doubt, physicians commonly interpret medical image conditioned on certainty like using phrase "prob…
Can Physician Judgment Enhance Model Trustworthiness? A Case Study on Predicting Pathological Lymph Nodes in Rectal Cancer
Kazuma Kobayashi, Yasuyuki Takamizawa, Mototaka Miyake +7
Explainability is key to enhancing artificial intelligence's trustworthiness in medicine. However, several issues remain concerning the actual benefit of explainable models for cli…
Expert Uncertainty and Severity Aware Chest X-Ray Classification by Multi-Relationship Graph Learning
Mengliang Zhang, Xinyue Hu, Lin Gu +5
Patients undergoing chest X-rays (CXR) often endure multiple lung diseases. When evaluating a patient's condition, due to the complex pathologies, subtle texture changes of differe…
Expert Knowledge-Aware Image Difference Graph Representation Learning for Difference-Aware Medical Visual Question Answering
Xinyue Hu, Lin Gu, Qiyuan An +6
To contribute to automating the medical vision-language model, we propose a novel Chest-Xray Difference Visual Question Answering (VQA) task. Given a pair of main and reference ima…
Sketch-based Medical Image Retrieval
Kazuma Kobayashi, Lin Gu, Ryuichiro Hataya +12
The amount of medical images stored in hospitals is increasing faster than ever; however, utilizing the accumulated medical images has been limited. This is because existing conten…
Interpretable Medical Image Visual Question Answering via Multi-Modal Relationship Graph Learning
Xinyue Hu, Lin Gu, Kazuma Kobayashi +6
Medical visual question answering (VQA) aims to answer clinically relevant questions regarding input medical images. This technique has the potential to improve the efficiency of m…
Decomposing Normal and Abnormal Features of Medical Images into Discrete Latent Codes for Content-Based Image Retrieval
Kazuma Kobayashi, Ryuichiro Hataya, Yusuke Kurose +5
In medical imaging, the characteristics purely derived from a disease should reflect the extent to which abnormal findings deviate from the normal features. Indeed, physicians ofte…