Qaisar Abbas

Summary

Publications

  1. doi request reprint Melanoma recognition framework based on expert definition of ABCD for dermoscopic images
    Qaisar Abbas
    Department of Computer Science, National Textile University, Faisalabad, 37610, Pakistan
    Skin Res Technol 19:e93-102. 2013
  2. doi request reprint Unsupervised skin lesions border detection via two-dimensional image analysis
    Qaisar Abbas
    Department of Computer Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
    Comput Methods Programs Biomed 104:e1-15. 2011
  3. doi request reprint Skin tumor area extraction using an improved dynamic programming approach
    Qaisar Abbas
    Department of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China
    Skin Res Technol 18:133-42. 2012
  4. doi request reprint Lesion border detection in dermoscopy images using dynamic programming
    Qaisar Abbas
    Department of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China
    Skin Res Technol 17:91-100. 2011
  5. ncbi request reprint Automatic skin tumour border detection for digital dermoscopy using a new digital image analysis scheme
    Q Abbas
    Department of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, PR China
    Br J Biomed Sci 67:177-83. 2010
  6. doi request reprint A feature-preserving hair removal algorithm for dermoscopy images
    Qaisar Abbas
    Department of Computer Science, National Textile University, Faisalabad, Pakistan
    Skin Res Technol 19:e27-36. 2013
  7. doi request reprint A perceptually oriented method for contrast enhancement and segmentation of dermoscopy images
    Qaisar Abbas
    Department of Computer Science, National Textile University, Faisalabad, Pakistan
    Skin Res Technol 19:e490-7. 2013
  8. doi request reprint Unified approach for lesion border detection based on mixture modeling and local entropy thresholding
    Qaisar Abbas
    Department of Computer Science, COMSATS Institute of Information Technology, Sahiwal, Pakistan
    Skin Res Technol 19:314-9. 2013
  9. doi request reprint Computer-aided pattern classification system for dermoscopy images
    Qaisar Abbas
    Department of Computer Science, National Textile University, Faisalaba 37610, Pakistan
    Skin Res Technol 18:278-89. 2012

Collaborators

Detail Information

Publications9

  1. doi request reprint Melanoma recognition framework based on expert definition of ABCD for dermoscopic images
    Qaisar Abbas
    Department of Computer Science, National Textile University, Faisalabad, 37610, Pakistan
    Skin Res Technol 19:e93-102. 2013
    ..However, the current computer-aided diagnostic (CAD) systems for classification between malignant and nevus lesions using the ABCD criteria are imperfect due to use of ineffective computerized techniques...
  2. doi request reprint Unsupervised skin lesions border detection via two-dimensional image analysis
    Qaisar Abbas
    Department of Computer Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
    Comput Methods Programs Biomed 104:e1-15. 2011
    ..The unsupervised border detection system increased the true detection rate (TDR) is 4.31% and reduced the false positive rate (FPR) of 5.28%...
  3. doi request reprint Skin tumor area extraction using an improved dynamic programming approach
    Qaisar Abbas
    Department of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China
    Skin Res Technol 18:133-42. 2012
    ..However, this task is complicated due to uneven illumination, artifacts present in the lesions and smooth areas or fuzzy borders of the desired regions...
  4. doi request reprint Lesion border detection in dermoscopy images using dynamic programming
    Qaisar Abbas
    Department of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China
    Skin Res Technol 17:91-100. 2011
    ..As a result, there is a need for robust methods to remove artifacts and detect lesion borders in dermoscopy images...
  5. ncbi request reprint Automatic skin tumour border detection for digital dermoscopy using a new digital image analysis scheme
    Q Abbas
    Department of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, PR China
    Br J Biomed Sci 67:177-83. 2010
    ..42% to 7.23%. The results have validated the integrated enhancement of numerous lesion border detections with the noise removal algorithm which may contribute to skin cancer classification...
  6. doi request reprint A feature-preserving hair removal algorithm for dermoscopy images
    Qaisar Abbas
    Department of Computer Science, National Textile University, Faisalabad, Pakistan
    Skin Res Technol 19:e27-36. 2013
    ..Currently, many hair-restoration algorithms have been developed, but most of these fail to identify hairs accurately and their removal technique is slow and disturbs the lesion's pattern...
  7. doi request reprint A perceptually oriented method for contrast enhancement and segmentation of dermoscopy images
    Qaisar Abbas
    Department of Computer Science, National Textile University, Faisalabad, Pakistan
    Skin Res Technol 19:e490-7. 2013
    ..Accordingly for lesion recognition, automatic melanoma border detection (MBD) is an initial as well as crucial task...
  8. doi request reprint Unified approach for lesion border detection based on mixture modeling and local entropy thresholding
    Qaisar Abbas
    Department of Computer Science, COMSATS Institute of Information Technology, Sahiwal, Pakistan
    Skin Res Technol 19:314-9. 2013
    ..In computerized diagnostic methods, automatic border detection is the first and crucial step...
  9. doi request reprint Computer-aided pattern classification system for dermoscopy images
    Qaisar Abbas
    Department of Computer Science, National Textile University, Faisalaba 37610, Pakistan
    Skin Res Technol 18:278-89. 2012
    ..To differentiate between benign and malignant lesions, the extraction of color, architectural order, symmetry of pattern and homogeneity (CASH) is a challenging task...