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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 …
Deep learning in digital pathology image analysis: a survey
Deep learning (DL) has achieved state-of-the-art performance in many digital pathology
analysis tasks. Traditional methods usually require hand-crafted domain-specific features …
analysis tasks. Traditional methods usually require hand-crafted domain-specific features …
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 …
Patch-based convolutional neural network for whole slide tissue image classification
Abstract Convolutional Neural Networks (CNN) are state-of-the-art models for many image
classification tasks. However, to recognize cancer subtypes automatically, training a CNN on …
classification tasks. However, to recognize cancer subtypes automatically, training a CNN on …
Crccn-net: Automated framework for classification of colorectal tissue using histopathological images
Colorectal cancer has a high mortality rate that continuously affects human life globally.
Early detection of it extends human life and helps in preventing disease. Histopathological …
Early detection of it extends human life and helps in preventing disease. Histopathological …
ImageCAS: A large-scale dataset and benchmark for coronary artery segmentation based on computed tomography angiography images
Cardiovascular disease (CVD) accounts for about half of non-communicable diseases.
Vessel stenosis in the coronary artery is considered to be the major risk of CVD. Computed …
Vessel stenosis in the coronary artery is considered to be the major risk of CVD. Computed …
Fast and accurate tumor segmentation of histology images using persistent homology and deep convolutional features
Tumor segmentation in whole-slide images of histology slides is an important step towards
computer-assisted diagnosis. In this work, we propose a tumor segmentation framework …
computer-assisted diagnosis. In this work, we propose a tumor segmentation framework …
DCAN: Deep contour-aware networks for object instance segmentation from histology images
In histopathological image analysis, the morphology of histological structures, such as
glands and nuclei, has been routinely adopted by pathologists to assess the malignancy …
glands and nuclei, has been routinely adopted by pathologists to assess the malignancy …
Colorectal histology tumor detection using ensemble deep neural network
With a mortality rate of approximately 33.33%, Colorectal cancer serves as the second most
prevalent malignant tumor type in the world. AI-guided clinical care/tool can help in reducing …
prevalent malignant tumor type in the world. AI-guided clinical care/tool can help in reducing …
Weakly supervised histopathology cancer image segmentation and classification
Labeling a histopathology image as having cancerous regions or not is a critical task in
cancer diagnosis; it is also clinically important to segment the cancer tissues and cluster …
cancer diagnosis; it is also clinically important to segment the cancer tissues and cluster …