Deep learning algorithms have become the first choice as an approach to medical image analysis, face recognition, and emotion recognition. In this survey, several deep-learning …
In histopathological image analysis, feature extraction for classification is a challenging task due to the diversity of histology features suitable for each problem as well as presence of …
Y Zheng, Z Jiang, F Xie, H Zhang, Y Ma, H Shi… - Pattern Recognition, 2017 - Elsevier
Feature extraction is a crucial and challenging aspect in the computer-aided diagnosis of breast cancer with histopathological images. In recent years, many machine learning …
MT McCann, JA Ozolek, CA Castro… - IEEE Signal …, 2014 - ieeexplore.ieee.org
Histology is the microscopic inspection of plant or animal tissue. It is a critical component in diagnostic medicine and a tool for studying the pathogenesis and biology of processes such …
CT Sari, C Gunduz-Demir - IEEE transactions on medical …, 2018 - ieeexplore.ieee.org
Histopathological examination is today's gold standard for cancer diagnosis. However, this task is time consuming and prone to errors as it requires a detailed visual inspection and …
The graph edit distance is a widely used distance measure for labelled graph. However, A★− GED, the standard approach for its exact computation, suffers from huge runtime and …
The multi-channel nature of digital histopathological images presents an opportunity to exploit the correlated color channel information for better image modeling. Inspired by recent …
Because of its flexibility, intuitiveness, and expressivity, the graph edit distance (GED) is one of the most widely used distance measures for labeled graphs. Since exactly computing …
Colon cancer causes deaths of about half a million people every year. Common method of its detection is histopathological tissue analysis, which, though leads to vital diagnosis, is …