Nuclei instance segmentation and classification in histology plays a major role in routine
pathology image examination, which enable morphological features analysis that further …

Nuclei instance segmentation is an integral step in digital pathology workflow as it is a
prerequisite for most downstream tasks such as patient survival analysis, precision …

The histopathological segmentation of nuclear types is a challenging task because nuclei
exhibit distinct morphologies, textures, and staining characteristics. Accurate segmentation …

In the cancer diagnosis pipeline, digital pathology plays an instrumental role in the
identification, staging, and grading of malignant areas on biopsy tissue specimens. High …

Deep convolution neural networks have been widely used in medical image analysis, such
as lesion identification in whole-slide images, cancer detection, and cell segmentation, etc …

The field of immunology is fundamental to our understanding of the intricate dynamics of the
tumor microenvironment. In particular, tumor-infiltrating lymphocyte (TIL) assessment …

Survival analysis is an integral part of medical statistics that is extensively utilized to
establish prognostic indices for mortality or disease recurrence, assess treatment efficacy …

Nuclear instance segmentation in histopathological images is a key procedure in
pathological diagnosis. In this regard, a typical class of solutions are deep learning-like …