Yu Zhou|Melvyn Smith|Lyndon Smith|Rob Warr

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Skin Research and Technology : Official Journal of International Society for Bioengineering and the Skin (ISBS) [And] International Society for Digital Imaging of Skin (ISDIS) [And] International Society for Skin Imaging (ISSI)|April 14, 2010

Using 3D differential forms to characterize a pigmented lesion in vivoYu Zhou, Melvyn Smith, Lyndon Smith, et al.

A new method describing border irregularity of pigmented lesionsYu Zhou, Melvyn Smith, Lyndon Smith, et al.

Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society|November 16, 2010

Enhanced 3D curvature pattern and melanoma diagnosisYu Zhou, Melvyn Smith, Lyndon Smith, et al.

Computer Methods and Programs in Biomedicine|April 16, 2022

Diabetes mellitus prediction and diagnosis from a data preprocessing and machine learning perspectiveChollette C Olisah, Lyndon Smith, Melvyn Smith

Unsupervised sub-segmentation for pigmented skin lesionsZhao Liu, Jiuai Sun, Melvyn Smith, et al.

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|October 19, 2011

Biological indexes based reflectional asymmetry for classifying cutaneous lesionsZhao Liu, Lyndon Smith, Jiuai Sun, et al.

Medical & Biological Engineering & Computing|March 23, 2012

Distribution quantification on dermoscopy images for computer-assisted diagnosis of cutaneous melanomasZhao Liu, Jiuai Sun, Lyndon Smith, et al.

Obtaining malignant melanoma indicators through statistical analysis of 3D skin surface disruptionsYi Ding, Lyndon Smith, Melvyn Smith, et al.

Computers in Industry|July 13, 2018

Photometric stereo for three-dimensional leaf venation extractionWenhao Zhang, Mark F Hansen, Melvyn Smith, et al.

Medical & Biological Engineering & Computing|May 8, 2015

Combination of 3D skin surface texture features and 2D ABCD features for improved melanoma diagnosisYi Ding, Nigel W John, Lyndon Smith, et al.

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Using 3D differential forms to characterize a pigmented lesion in vivoYu Zhou, Melvyn Smith, Lyndon Smith, et al.

A new method describing border irregularity of pigmented lesionsYu Zhou, Melvyn Smith, Lyndon Smith, et al.

Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society|November 16, 2010

Enhanced 3D curvature pattern and melanoma diagnosisYu Zhou, Melvyn Smith, Lyndon Smith, et al.

Computer Methods and Programs in Biomedicine|April 16, 2022

Diabetes mellitus prediction and diagnosis from a data preprocessing and machine learning perspectiveChollette C Olisah, Lyndon Smith, Melvyn Smith

Unsupervised sub-segmentation for pigmented skin lesionsZhao Liu, Jiuai Sun, Melvyn Smith, et al.

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|October 19, 2011

Biological indexes based reflectional asymmetry for classifying cutaneous lesionsZhao Liu, Lyndon Smith, Jiuai Sun, et al.

Medical & Biological Engineering & Computing|March 23, 2012

Distribution quantification on dermoscopy images for computer-assisted diagnosis of cutaneous melanomasZhao Liu, Jiuai Sun, Lyndon Smith, et al.

Obtaining malignant melanoma indicators through statistical analysis of 3D skin surface disruptionsYi Ding, Lyndon Smith, Melvyn Smith, et al.

Computers in Industry|July 13, 2018

Photometric stereo for three-dimensional leaf venation extractionWenhao Zhang, Mark F Hansen, Melvyn Smith, et al.

Medical & Biological Engineering & Computing|May 8, 2015

Combination of 3D skin surface texture features and 2D ABCD features for improved melanoma diagnosisYi Ding, Nigel W John, Lyndon Smith, et al.

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