Color calibration model of skin lesion images for computer-aided diagnostic

2013 ◽  
Author(s):  
L.A. Nowak ◽  
M.P. Pawlowski ◽  
K. Grzesiak-Kopec ◽  
M.J. Ogorzalek
Keyword(s):  
Skin Lesion ◽  
Calibration Model ◽  
Color Calibration ◽  
Computer Aided

DermaDL: Advanced Convolutional Neural Networks for Computer-Aided Skin-Lesion Classification

2021 ◽  
Vol 2 (4) ◽  
Author(s):  
Daniel M. Lima ◽  
Jose F. Rodrigues-Jr ◽  
Bruno Brandoli ◽  
Lorraine Goeuriot ◽  
Sihem Amer-Yahia
Keyword(s):  
Neural Networks ◽  
Skin Lesion ◽  
Convolutional Neural Networks ◽  
Computer Aided ◽  
Lesion Classification

Intelligent Content-Based Dermoscopic Image Retrieval with Relevance Feedback for Computer-Aided Melanoma Diagnosis

2017 ◽  
Vol 10 (1) ◽  
pp. 85-108 ◽  
Author(s):  
Khadidja Belattar ◽  
Sihem Mostefai ◽  
Amer Draa
Keyword(s):  
Skin Lesion ◽  
Image Retrieval ◽  
Relevance Feedback ◽  
Query Image ◽  
Melanoma Diagnosis ◽  
Computer Aided ◽  
Histogram Intersection ◽  
Dermoscopic Image ◽  
Image Query ◽  
Aided Diagnosis

The use of Computer-Aided Diagnosis in dermatology raises the necessity of integrating Content-Based Image Retrieval (CBIR) technologies. The latter could be helpful to untrained users as a decision support system for skin lesion diagnosis. However, classical CBIR systems perform poorly due to semantic gap. To alleviate this problem, we propose in this paper an intelligent Content-Based Dermoscopic Image Retrieval (CBDIR) system with Relevance Feedback (RF) for melanoma diagnosis that exhibits: efficient and accurate image retrieval as well as visual features extraction that is independent of any specific diagnostic method. After submitting a query image, the proposed system uses linear kernel-based active SVM, combined with histogram intersection-based similarity measure to retrieve the K most similar skin lesion images. The dominant (melanoma, benign) class in this set will be identified as the image query diagnosis. Extensive experiments conducted on our system using a 1097 image database show that the proposed scheme is more effective than CBDIR without the assistance of RF.

Computer Aided Skin Lesion Diagnosis with Humans in the Loop

2012 ◽  
pp. 266-274 ◽  
Author(s):  
Orod Razeghi ◽  
Guoping Qiu ◽  
Hywel Williams ◽  
Kim Thomas
Keyword(s):  
Skin Lesion ◽  
Computer Aided

A LCD Color Calibration Model Based on Gamut-Division Algorithm

2015 ◽  
Vol 731 ◽  
pp. 49-52
Author(s):  
Yin Zhang ◽  
Mao Hai Lin
Keyword(s):  
Liquid Crystal Display ◽  
Color Space ◽  
Color Difference ◽  
Calibration Method ◽  
Calibration Model ◽  
Division Algorithm ◽  
Model Based ◽  
Color Calibration ◽  
Soft Proofing ◽  
Color Rendering

The accuracy of color appearance of displayed image on a liquid crystal display (LCD) is the fundamental to guarantee good results in the soft proofing and cross-media color reproduction. Since the color rendering mechanism of LCDs is different from cathode-ray tube (CRT) displays, the traditional color calibration method cannot turn a very good result. In this paper, a LCD color calibration model based on gamut-division algorithm is proposed using spline method through the analysis of its color rendering mechanism. The monitor 3D gamut is firstly divided along the axis of L* in CIELAB color space according to the hue angle, and then an optimal color calibration matrix of the sub-gamut is computed with mathematical method. The experimental results show that the average color difference, the maximum color difference and hue shift are reduced compared with the traditional method.

Directional Vector-Based Skin Lesion Segmentation — A Novel Approach to Skin Segmentation

2020 ◽  
Vol 20 (03) ◽  
pp. 2050021
Author(s):  
P. Nikesh ◽  
G. Raju
Keyword(s):  
Skin Lesion ◽  
Automatic Segmentation ◽  
High Accuracy ◽  
Lesion Segmentation ◽  
Seed Point ◽  
Skin Segmentation ◽  
Novel Approach ◽  
Segmentation Algorithms ◽  
Computer Aided ◽  
Aided Diagnosis

Efficient skin lesion segmentation algorithms are required for computer aided diagnosis of skin cancer. Several algorithms were proposed for skin lesion segmentation. The existing algorithms are short of achieving ideal performance. In this paper, a novel semi-automatic segmentation algorithm is proposed. The fare concept of the proposed is 8-directional search based on threshold for lesion pixel, starting from a user provided seed point. The proposed approach is tested on 200 images from PH2 and 900 images from ISBI 2016 datasets. In comparison to a chosen set of algorithms, the proposed approach gives high accuracy and specificity values. A significant advantage of the proposed method is the ability to deal with discontinuities in the lesion.

Computer-aided catchment-calibration model

1993 ◽  
Vol 17 (3) ◽  
pp. 147-154 ◽  
Author(s):  
Shie-Yui Liong ◽  
Yaacob Ibrahim ◽  
Weng Tat Chan ◽  
Chee Liang Law
Keyword(s):  
Calibration Model ◽  
Computer Aided
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