Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …

Real-time chemical process monitoring, analysis, and control have become increasingly
important to multi-phase flow process research and development and attracted overt …

Accurate segmentation of nuclei plays a critical role in pathology since assessments and
diagnoses are mainly based on the recognition, measurement, and counting of nuclei …

Multi-class cell nuclei detection is a fundamental prerequisite in the diagnosis of
histopathology. It is critical to efficiently locate and identify cells with diverse morphology and …

Nuclear instance segmentation has been critical for pathology image analysis in medical
science, eg, cancer diagnosis. Current methods typically adopt pixel-wise optimization for …

Weakly supervised segmentation methods have garnered considerable attention due to
their potential to alleviate the need for labor-intensive pixel-level annotations during model …

In digital pathology, precise nuclei segmentation is pivotal yet challenged by the diversity of
tissue types, staining protocols, and imaging conditions. Recently, the segment anything …

Nuclei segmentation is a crucial task for whole slide image analysis in digital pathology.
Generally, the segmentation performance of fully-supervised learning heavily depends on …

Microscopic evaluation of glands in the colon is of utmost importance in the diagnosis of
inflammatory bowel disease and cancer. When properly trained, deep learning pipelines …

This manuscript gives a brief description of the algorithm used to participate in CoNIC
Challenge 2022. After the baseline was made available, we follow the method in it and …