Histopathological image analysis: A review
MN Gurcan, LE Boucheron, A Can… - IEEE reviews in …, 2009 - ieeexplore.ieee.org
Over the past decade, dramatic increases in computational power and improvement in
image analysis algorithms have allowed the development of powerful computer-assisted …
image analysis algorithms have allowed the development of powerful computer-assisted …
Artificial intelligence in the management of glioma: era of personalized medicine
Purpose: Artificial intelligence (AI) has accelerated novel discoveries across multiple
disciplines including medicine. Clinical medicine suffers from a lack of AI-based …
disciplines including medicine. Clinical medicine suffers from a lack of AI-based …
Breast cancer histopathological image classification using a hybrid deep neural network
Even with the rapid advances in medical sciences, histopathological diagnosis is still
considered the gold standard in diagnosing cancer. However, the complexity of …
considered the gold standard in diagnosing cancer. However, the complexity of …
Cgc-net: Cell graph convolutional network for grading of colorectal cancer histology images
Colorectal cancer (CRC) grading is typically carried out by assessing the degree of gland
formation within histology images. To do this, it is important to consider the overall tissue …
formation within histology images. To do this, it is important to consider the overall tissue …
[图书][B] The structure of complex networks: theory and applications
E Estrada - 2012 - books.google.com
This book deals with the analysis of the structure of complex networks by combining results
from graph theory, physics, and pattern recognition. The book is divided into two parts. 11 …
from graph theory, physics, and pattern recognition. The book is divided into two parts. 11 …
Improved automatic detection and segmentation of cell nuclei in histopathology images
Y Al-Kofahi, W Lassoued, W Lee… - IEEE Transactions on …, 2009 - ieeexplore.ieee.org
Automatic segmentation of cell nuclei is an essential step in image cytometry and histometry.
Despite substantial progress, there is a need to improve accuracy, speed, level of …
Despite substantial progress, there is a need to improve accuracy, speed, level of …
Towards large-scale histopathological image analysis: Hashing-based image retrieval
Automatic analysis of histopathological images has been widely utilized leveraging
computational image-processing methods and modern machine learning techniques. Both …
computational image-processing methods and modern machine learning techniques. Both …
Emerging themes in image informatics and molecular analysis for digital pathology
R Bhargava, A Madabhushi - Annual review of biomedical …, 2016 - annualreviews.org
Pathology is essential for research in disease and development, as well as for clinical
decision making. For more than 100 years, pathology practice has involved analyzing …
decision making. For more than 100 years, pathology practice has involved analyzing …
Deep weakly-supervised learning methods for classification and localization in histology images: a survey
Using deep learning models to diagnose cancer from histology data presents several
challenges. Cancer grading and localization of regions of interest (ROIs) in these images …
challenges. Cancer grading and localization of regions of interest (ROIs) in these images …
The natural and engineered 3D microenvironment as a regulatory cue during stem cell fate determination
The concept of using stem cells as self-renewing sources of healthy cells in regenerative
medicine has existed for decades, but most applications have yet to achieve clinical …
medicine has existed for decades, but most applications have yet to achieve clinical …