The analysis of glandular morphology within colon histopathology images is an important
step in determining the grade of colon cancer. Despite the importance of this task, manual …

Objective: A new image instance segmentation method is proposed to segment individual
glands (instances) in colon histology images. This process is challenging since the glands …

Segmentation of histopathology sections is a necessary preprocessing step for digital
pathology. Due to the large variability of biological tissue, machine learning techniques have …

Colorectal adenocarcinoma originating in intestinal glandular structures is the most common
form of colon cancer. In clinical practice, the morphology of intestinal glands, including …

In pathological image analysis, determination of gland morphology in histology images of
the colon is essential to determine the grade of colon cancer. However, manual …

In this paper, we propose a new image instance segmentation method that segments
individual glands (instances) in colon histology images. This is a task called instance …

The accurate gland segmentation from digitized H&E (hematoxylin and eosin) histology
images with a wide range of histologic grades of cancer is quite challenging. The …

Gland segmentation is an important step to automate the analysis of biopsies that contain
glandular structures. However, this remains a challenging problem as the variation in …

Colonic adenocarcinoma is a disease severely endangering human life caused by mucosal
epidermal carcinogenesis. The segmentation of potentially cancerous glands is the key in …

We investigate glandular structure segmentation in colon histology images as a window-
based classification problem. We compare and combine methods based on fine-tuned …