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 …
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 …
[LIVRE][B] Discrete calculus: Applied analysis on graphs for computational science
LJ Grady, JR Polimeni - 2010 - Springer
The field of discrete calculus, also known as" discrete exterior calculus", focuses on finding a
proper set of definitions and differential operators that make it possible to operate the …
proper set of definitions and differential operators that make it possible to operate the …
[PDF][PDF] Automated cancer diagnosis based on histopathological images: a systematic survey
In traditional cancer diagnosis, pathologists examine biopsies to make diagnostic
assessments largely based on cell morphology and tissue distribution. However, this is …
assessments largely based on cell morphology and tissue distribution. However, this is …
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 …
Color graphs for automated cancer diagnosis and grading
D Altunbay, C Cigir, C Sokmensuer… - IEEE Transactions …, 2009 - ieeexplore.ieee.org
This paper reports a new structural method to mathematically represent and quantify a tissue
for the purpose of automated and objective cancer diagnosis and grading. Unlike the …
for the purpose of automated and objective cancer diagnosis and grading. Unlike the …
Effective graph classification based on topological and label attributes
Graph classification is an important data mining task, and various graph kernel methods
have been proposed recently for this task. These methods have proven to be effective, but …
have been proposed recently for this task. These methods have proven to be effective, but …
A recent survey on colon cancer detection techniques
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 …
its detection is histopathological tissue analysis, which, though leads to vital diagnosis, is …
A survey on automated cancer diagnosis from histopathology images
Detecting cancer at an early stage is useful in better patient prognosis and treatment
planning. Even though there are several preliminary tests and non-invasive procedures that …
planning. Even though there are several preliminary tests and non-invasive procedures that …
Graph run-length matrices for histopathological image segmentation
The histopathological examination of tissue specimens is essential for cancer diagnosis and
grading. However, this examination is subject to a considerable amount of observer …
grading. However, this examination is subject to a considerable amount of observer …