Computer-aided Diagnosis Systems for Prostate Cancer: A Comprehensive Study

被引:0
作者
Garg G. [1 ]
机构
[1] Department of Computer Science and Engineering, Chitkara School of Engineering and Technology, Chitkara University, Himachal Pradesh, Baddi
关键词
ACS; CADx; Classification; MRI; Prostate cancer; Segmentation;
D O I
10.2174/1573405620666230522151406
中图分类号
学科分类号
摘要
The American Cancer Society (ACS) reported in their Cancer Facts and Figures 2021 that prostate cancer (PCa) is the second leading cause of death among American men, with an average age of diagnosis being 66 years. This health issue predominantly affects older men and poses a significant challenge for radiologists, urologists, and oncologists when it comes to accurately diagnosing and treating it in a timely manner. Detecting PCa with precision and on time is crucial for proper treatment planning and reducing the increasing mortality rate. This paper focuses on a computer-aided diagnosis (CADx) system, which is discussed in detail with different phases specific to PCa. Each phase of CADx is comprehensively analyzed and evaluated based on recent state-of-the-art techniques in both quantitative and qualitative aspects. This study outlines significant research gaps and findings for every phase of CADx, providing valuable insights to biomedical engineers and researchers. © 2024 The Author(s). Published by Bentham Science Publisher.
引用
收藏
相关论文
共 50 条
  • [21] Clinical evaluation of a computer-aided diagnosis system for determining cancer aggressiveness in prostate MRI
    Litjens, Geert J. S.
    Barentsz, Jelle O.
    Karssemeijer, Nico
    Huisman, Henkjan J.
    EUROPEAN RADIOLOGY, 2015, 25 (11) : 3187 - 3199
  • [22] Computer-aided Detection of Prostate Cancer on Tissue Sections
    Peng, Yahui
    Jiang, Yulei
    Chuang, Shang-Tian
    Yang, Ximing J.
    APPLIED IMMUNOHISTOCHEMISTRY & MOLECULAR MORPHOLOGY, 2009, 17 (05): : 442 - 450
  • [23] Computer-aided diagnosis of prostate cancer with emphasis on ultrasound-based approaches: A review
    Moradi, Mehdi
    Mousavi, Parvin
    Abolmaesumi, Purang
    ULTRASOUND IN MEDICINE AND BIOLOGY, 2007, 33 (07) : 1010 - 1028
  • [24] Clinical evaluation of a computer-aided diagnosis system for determining cancer aggressiveness in prostate MRI
    Geert J. S. Litjens
    Jelle O. Barentsz
    Nico Karssemeijer
    Henkjan J. Huisman
    European Radiology, 2015, 25 : 3187 - 3199
  • [25] Recent innovations in machine learning for skin cancer lesion analysis and classification: A comprehensive analysis of computer-aided diagnosis
    Zareen, Syeda Shamaila
    Hossain, Md Shamim
    Wang, Junsong
    Kang, Yan
    PRECISION MEDICAL SCIENCES, 2025, 14 (01): : 15 - 40
  • [26] Computer-Aided Diagnosis and Lipidomics Analysis to Detect and Treat Breast Cancer
    Meyer-Baese, Anke
    Retter, Felix
    Steinbruecker, Frank
    Goerke, Robert
    Burgeth, Bernhard
    Schlossbauer, Thomas
    INDEPENDENT COMPONENT ANALYSES, WAVELETS, NEURAL NETWORKS, BIOSYSTEMS, AND NANOENGINEERING VIII, 2010, 7703
  • [27] Update on the potential of computer-aided diagnosis for breast cancer
    Giger, Maryellen L.
    FUTURE ONCOLOGY, 2010, 6 (01) : 1 - 4
  • [28] NUCLEI SEGMENTATION FOR COMPUTER-AIDED DIAGNOSIS OF BREAST CANCER
    Kowal, Marek
    Filipczuk, Pawel
    INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE, 2014, 24 (01) : 19 - 31
  • [29] Computer-aided diagnosis of renal lesions in CT images: A comprehensive survey and future prospects
    Kaur, Ravinder
    Juneja, Mamta
    Mandal, A. K.
    COMPUTERS & ELECTRICAL ENGINEERING, 2019, 77 : 423 - 434
  • [30] Computer-aided diagnosis of liver tumors on computed tomography images
    Chang, Chin-Chen
    Chen, Hong-Hao
    Chang, Yeun-Chung
    Yang, Ming-Yang
    Lo, Chung-Ming
    Ko, Wei-Chun
    Lee, Yee-Fan
    Liu, Kao-Lang
    Chang, Ruey-Feng
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2017, 145 : 45 - 51