Deep learning-based methods have become the dominant methodology in medical image
processing with the advancement of deep learning in natural image classification, detection …

Multi-label classification (MLC) can attach multiple labels on single image, and has
achieved promising results on medical images. But existing MLC methods still face …

Optical coherence tomography (OCT) is a new type of tomography that has experienced
rapid development and potential in recent years. It is playing an increasingly important role …

Thyroid nodules are one of the most common nodular lesions. The incidence of thyroid
cancer has increased rapidly in the past three decades and is one of the cancers with the …

Automatic and accurate classification of retinal optical coherence tomography (OCT) images
is essential to assist physicians in diagnosing and grading pathological changes in …

Optical coherence tomography (OCT) is an imaging modality used to obtain a cross-
sectional image of the retina for retinal disease diagnosis. Modern diagnosis systems use …

Glioma grading during surgery can help clinical treatment planning and prognosis, but
intraoperative pathological examination of frozen sections is limited by the long processing …

The fusion of multi-modal data, eg, medical images and genomic profiles, can provide
complementary information and further benefit disease diagnosis. However, multi-modal …

Ovarian cancer is one of the most harmful gynecological diseases. Detecting ovarian tumors
in early stage with computer-aided techniques can efficiently decrease the mortality rate …

There have been few efforts made to automate the cytomorphological categorization of bone
marrow cells. For bone marrow cell categorization, deep-learning algorithms have been …