Nuclear-derived morphological features and biomarkers provide relevant insights regarding
the tumour microenvironment, while also allowing diagnosis and prognosis in specific …

In histopathology, nuclei within images hold vital diagnostic information. Automated
segmentation of nuclei can alleviate pathologists' workload and enhance diagnostic …

Objective: Nuclei segmentation is a crucial pre-task for pathological microenvironment
quantification. However, the acquisition of manually precise nuclei annotations for improving …

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 …

Histopathology, vital in diagnosing medical conditions, especially in cancer research, relies
on analyzing histopathology images (HIs). Nuclei segmentation, a key task, involves …

Abstract The Whole Slide Image (WSI) is a pathological image with Hematoxylin & Eosin
staining. The low-contrast color staining will bring a challenge on analysis. We propose …

The segmentation and classification of nuclei in haematoxylin and eosin-stained images is
critical for diagnosing cancer and other disorders. Developing automated methods is …

Segmentation of nuclei in histopathology images with high accuracy is crucial for the
diagnosis and prognosis of cancer and other diseases. Using Artificial Intelligence (AI) in the …

El hígado, crucial para la digestión y el sistema circulatorio, contiene diversos tipos de
células con variaciones morfológicas y nucleares. Comprender su funcionamiento a nivel …