3 accepted papers
Defocus blurring is a prevalent problem in digital pathology imaging, which degrades the quality and accuracy of biomedical research and clinical diagnosis. Existing deblurring methods are mostly based on one-to-one image translation models, which require multiple models to handle different defocus…
The automation of radiology report generation (RRG) holds immense potential to alleviate radiologists’ workloads and improve diagnostic accuracy. Despite advancements in image captioning and vision-language pretraining, RRG remains challenging due to the lengthy and complex nature of radiology repor…
Pathological examination is regarded as the gold standard for cancer diagnosis in clinical medicine. Gigapixel histopathological images play an important role in developing automatic pathology diagnosis systems. Because of the expensive cost of pixel-level annotation, deep multiple instance learning…