Incorporating Colour Information for Computer-Aided Diagnosis of Melanoma from Dermoscopy Images: A Retrospective Survey and Critical Analysis

被引:13
|
作者
Madooei, Ali [1 ]
Drew, Mark S. [1 ]
机构
[1] Simon Fraser Univ, Sch Comp Sci, Burnaby, BC, Canada
关键词
D O I
10.1155/2016/4868305
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Cutaneous melanoma is the most life-threatening form of skin cancer. Although advanced melanoma is often considered as incurable, if detected and excised early, the prognosis is promising. Today, clinicians use computer vision in an increasing number of applications to aid early detection ofmelanoma through dermatological image analysis (dermoscopy images, in particular). Colour assessment is essential for the clinical diagnosis of skin cancers. Due to this diagnostic importance, many studies have either focused on or employed colour features as a constituent part of their skin lesion analysis systems. These studies range from using low-level colour features, such as simple statistical measures of colours occurring in the lesion, to availing themselves of high-level semantic features such as the presence of blue-white veil, globules, or colour variegation in the lesion. This paper provides a retrospective survey and critical analysis of contributions in this research direction.
引用
收藏
页数:18
相关论文
共 50 条
  • [21] Computer-Aided Breast Cancer Diagnosis from Thermal Images Using Transfer Learning
    Cabioglu, Cagri
    Ogul, Hasan
    [J]. BIOINFORMATICS AND BIOMEDICAL ENGINEERING (IWBBIO 2020), 2020, 12108 : 716 - 726
  • [22] Computer-aided diagnosis software for vulvovaginal candidiasis detection from Pap smear images
    Momenzadeh, Mohammadreza
    Vard, Alireza
    Talebi, Ardeshir
    Mehri Dehnavi, Alireza
    Rabbani, Hossein
    [J]. MICROSCOPY RESEARCH AND TECHNIQUE, 2018, 81 (01) : 13 - 21
  • [23] Clinical Utility of Computer-Aided Diagnosis of Vertebral Fractures From Computed Tomography Images
    Kolanu, Nithin
    Silverstone, Elizabeth J.
    Ho, Bao H.
    Pham, Hiep
    Hansen, Ash
    Pauley, Emma
    Quirk, Anna R.
    Sweeney, Sarah C.
    Center, Jacqueline R.
    Pocock, Nicholas A.
    [J]. JOURNAL OF BONE AND MINERAL RESEARCH, 2020, 35 (12) : 2307 - 2312
  • [24] Computer-Aided Diagnosis of Melanoma Using Border- and Wavelet-Based Texture Analysis
    Garnavi, Rahil
    Aldeen, Mohammad
    Bailey, James
    [J]. IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, 2012, 16 (06): : 1239 - 1252
  • [25] Tuberculosis Detection from Chest Radiographs: A Comprehensive Survey on Computer-aided Diagnosis Techniques
    Hooda, Rahul
    Mittal, Ajay
    Sofat, Sanjeev
    [J]. CURRENT MEDICAL IMAGING, 2018, 14 (04) : 506 - 520
  • [26] Computer-aided diagnosis (CAD) system based on multi-layer feature fusion network for skin lesion recognition in dermoscopy images
    Ibtissam Bakkouri
    Karim Afdel
    [J]. Multimedia Tools and Applications, 2020, 79 : 20483 - 20518
  • [27] Computer-aided analysis of radiological images for cancer diagnosis: performance analysis on benchmark datasets, challenges, and directions
    Alyami, Jaber
    [J]. EJNMMI REPORTS, 2024, 8 (01)
  • [28] Computer-aided analysis of radiological images for cancer diagnosis: performance analysis on benchmark datasets, challenges, and directions
    Jaber Alyami
    [J]. EJNMMI Reports, 8
  • [29] Computer-aided diagnosis (CAD) system based on multi-layer feature fusion network for skin lesion recognition in dermoscopy images
    Bakkouri, Ibtissam
    Afdel, Karim
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2020, 79 (29-30) : 20483 - 20518
  • [30] Computer-Aided Diagnosis for Detection of Lacunar Infarcts on MR Images: ROC Analysis of Radiologists' Performance
    Uchiyama, Yoshikazu
    Asano, Takahiko
    Kato, Hiroki
    Hara, Takeshi
    Kanematsu, Masayuki
    Hoshi, Hiroaki
    Iwama, Toru
    Fujita, Hiroshi
    [J]. JOURNAL OF DIGITAL IMAGING, 2012, 25 (04) : 497 - 503