MILD-Net: Minimal information loss dilated network for gland instance segmentation in colon histology images
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 …
step in determining the grade of colon cancer. Despite the importance of this task, manual …
[HTML][HTML] Segmentation and classification of colon glands with deep convolutional neural networks and total variation regularization
Segmentation of histopathology sections is a necessary preprocessing step for digital
pathology. Due to the large variability of biological tissue, machine learning techniques have …
pathology. Due to the large variability of biological tissue, machine learning techniques have …
Gland instance segmentation using deep multichannel neural networks
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 …
glands (instances) in colon histology images. This process is challenging since the glands …
Gland segmentation in colon histology images: The glas challenge contest
Colorectal adenocarcinoma originating in intestinal glandular structures is the most common
form of colon cancer. In clinical practice, the morphology of intestinal glands, including …
form of colon cancer. In clinical practice, the morphology of intestinal glands, including …
Gland instance segmentation by deep multichannel side supervision
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 …
individual glands (instances) in colon histology images. This is a task called instance …
Gland segmentation in colorectal cancer histopathological images using U-net inspired convolutional network
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 …
images with a wide range of histologic grades of cancer is quite challenging. The …
Automatic segmentation of colon glands using object-graphs
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 …
glandular structures. However, this remains a challenging problem as the variation in …
Two path gland segmentation algorithm of colon pathological image based on local semantic guidance
Colonic adenocarcinoma is a disease severely endangering human life caused by mucosal
epidermal carcinogenesis. The segmentation of potentially cancerous glands is the key in …
epidermal carcinogenesis. The segmentation of potentially cancerous glands is the key in …
Gland segmentation in colon histology images using hand-crafted features and convolutional neural networks
We investigate glandular structure segmentation in colon histology images as a window-
based classification problem. We compare and combine methods based on fine-tuned …
based classification problem. We compare and combine methods based on fine-tuned …
DCAN: deep contour-aware networks for accurate gland segmentation
The morphology of glands has been used routinely by pathologists to assess the
malignancy degree of adenocarcinomas. Accurate segmentation of glands from histology …
malignancy degree of adenocarcinomas. Accurate segmentation of glands from histology …