Abstract
Abundant accumulation of digital histopathological images has led to the increased demand for their analysis, such as computer-aided diagnosis using machine learning techniques. However, digital pathological images and related tasks have some issues to be considered. In this mini-review, we introduce the application of digital pathological image analysis using machine learning algorithms, address some problems specific to such analysis, and propose possible solutions.
Highlights
Pathology diagnosis has been performed by a human pathologist observing the stained specimen on the slide glass using a microscope
We describe the application of digital pathological image analysis using machine learning algorithms, and its problems specific to digital pathological image analysis and the possible solutions
Since the overwhelming victory of the team using deep learning at ImageNet Large Scale Visual Recognition Competition (ILSVRC) 2012 [8], most of the image recognition techniques have been replaced by deep learning
Summary
Pathology diagnosis has been performed by a human pathologist observing the stained specimen on the slide glass using a microscope. As a large number of WSI are being accumulated, attempts have been made to analyze WSIs using digital image analysis based on machine learning algorithms to assist tasks including diagnosis. The goal of feature extraction is to extract useful information for machine learning tasks Various local features such as gray level co-occurrence Matrix (GLCM) and local binary pattern (LBP) have been used for histopathological image analysis, but deep learning algorithms such as convolutional neural network [9,10,12,13,14] starts the analysis from feature extraction. Machine learning techniques often used in digital pathology image analysis are divided into supervised learning and unsupervised learning. Since the amount of data is enormous, it is not realistic for pathologists and researchers to analyze all the relationships manually by looking at the specimens This is where the machine learning technology comes in.
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