Abstract
Prostate cancer is one of the most identified cancers and second most prevalent among cancer-related deaths of men worldwide. Early diagnosis and treatment are substantial to stop or handle the increase and spread of cancer cells in the body. Histopathological image diagnosis is a gold standard for detecting prostate cancer as it has different visual characteristics but interpreting those type of images needs a high level of expertise and takes too much time. One of the ways to accelerate such an analysis is by employing artificial intelligence (AI) through the use of computer-aided diagnosis (CAD) systems. The recent developments in artificial intelligence along with its sub-fields of conventional machine learning and deep learning provide new insights to clinicians and researchers, and an abundance of research is presented specifically for histopathology images tailored for prostate cancer. However, there is a lack of comprehensive surveys that focus on prostate cancer using histopathology images. In this paper, we provide a very comprehensive review of most, if not all, studies that handled the prostate cancer diagnosis using histopathological images. The survey begins with an overview of histopathological image preparation and its challenges. We also briefly review the computing techniques that are commonly applied in image processing, segmentation, feature selection, and classification that can help in detecting prostate malignancies in histopathological images.
Highlights
Prostate cancer is one of the most common cancers all over the world and considered the second cause of cancer deaths in several countries [1,2]
Many surveys have been published in recent years reviewing histopathological image analysis covering its history, and detailed information of general artificial intelligence techniques [7,8,12,31,36,37,38,39,40,41,42]; the main limitation is the lack of comprehensive surveys of histopathological image analysis that focus on prostate cancer [1,43,44]
More than 28% of cancers in men arise in the prostate gland, causing prostate cancer, and detection of this type has a high priority in cancer research
Summary
Prostate cancer is one of the most common cancers all over the world and considered the second cause of cancer deaths in several countries [1,2]. Many surveys have been published in recent years reviewing histopathological image analysis covering its history, and detailed information of general artificial intelligence techniques [7,8,12,31,36,37,38,39,40,41,42]; the main limitation is the lack of comprehensive surveys of histopathological image analysis that focus on prostate cancer [1,43,44].
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