Can automated dermoscopy image analysis instruments provide added benefit for the dermatologist? A study comparing the results of three systems

Perrinaud, A.; Gaide, Olivier; French, Lars E.; Saurat, Jean‐Hilaire; Marghoob, Ashfaq A.; Braun, Ralph P.

doi:10.1111/j.1365-2133.2007.08168.x

Cited by 61 publications

(50 citation statements)

References 20 publications

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“…CADx has been demonstrated to increase the diagnostic accuracy of trainees in the field of radiology. In dermatology, the benefits of the integration of CADx into the clinical diagnosis of pigmented skin lesions for dermatologists remain under investigation [26], [30], [31].…”

Section: Introductionmentioning

confidence: 99%

Computer-Aided Diagnosis of Skin Lesions Using Conventional Digital Photography: A Reliability and Feasibility Study

et al. 2013

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BackgroundComputer-aided diagnosis (CADx) software that provides a second opinion has been widely used to assist physicians with various tasks. In dermatology, however, CADx has been mostly limited to melanoma or melanocytic skin cancer diagnosis. The frequency of non-melanocytic skin cancers and the accessibility of regular digital macrographs have raised interest in developing CADx for broader applications.ObjectivesTo investigate the feasibility of using CADx to diagnose both melanocytic and non-melanocytic skin lesions based on conventional digital photographic images.MethodsThis study was approved by an institutional review board, and the requirement to obtain informed consent was waived. In total, 769 conventional photographs of melanocytic and non-melanocytic skin lesions were retrospectively reviewed and used to develop a CADx system. Conventional and new color-related image features were developed to classify the lesions as benign or malignant using support vector machines (SVMs). The performance of CADx was compared with that of dermatologists.ResultsThe clinicians' overall sensitivity, specificity, and accuracy were 83.33%, 85.88%, and 85.31%, respectively. New color correlation and principal component analysis (PCA) features improved the classification ability of the baseline CADx (p = 0.001). The estimated area under the receiver operating characteristic (ROC) curve (Az) of the proposed CADx system was 0.949, with a sensitivity and specificity of 85.63% and 87.65%, respectively, and a maximum accuracy of 90.64%.ConclusionsWe have developed an effective CADx system to classify both melanocytic and non-melanocytic skin lesions using conventional digital macrographs. The system's performance was similar to that of dermatologists at our institute. Through improved feature extraction and SVM analysis, we found that conventional digital macrographs were feasible for providing useful information for CADx applications. The new color-related features significantly improved CADx applications for skin cancer.

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Section: Introductionmentioning

confidence: 99%

Computer-Aided Diagnosis of Skin Lesions Using Conventional Digital Photography: A Reliability and Feasibility Study

et al. 2013

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“…37,38 A recent trial comparing three commercially available systems for diagnostic accuracy found that each one tended to overdiagnose suspect melanocytic lesions as melanoma and questioned whether they were ready to be used in clinical practice. 39 Nonetheless, logic dictates that with proficient training and programming, automated systems will eventually match, if not exceed, clinical diagnostic accuracy.…”

Section: Computer-assisted Diagnosis Of Pigmented Lesionsmentioning

confidence: 99%

Current and emerging technologies in melanoma diagnosis: the state of the art

Psaty

Halpern

2009

Clinics in Dermatology

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Relative to other specialties, dermatologists have been slow to adopt advanced technologic diagnostic aids. After all, most skin disease can be diagnosed by simple visual inspection, and the skin is readily accessible for a diagnostic biopsy. Diagnostic aids such as total body photography and dermoscopy improve the clinician's ability to diagnose melanoma beyond unaided visual inspection, however, and are now considered mainstream methods for early detection. Emerging technologies such as in vivo reflectance confocal microscopy are currently being investigated to determine their utility for noninvasive diagnosis of melanoma. This review summarizes the currently available cutaneous imaging devices and new frontiers in noninvasive diagnosis of skin disease. We anticipate that multimodal systems that combine different imaging technologies will further improve our ability to detect, at the bedside, melanoma at an earlier stage.

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“…Automated analysis of edges, colors, and shape of the lesion relies upon an accurate segmentation and is an important first step in any computer aided diagnosis system. Indeed, most commercially available systems show a great variability in reliability and specificity in the diagnostic process, and the image segmentation also varies greatly [3]. Irregular shape, nonuniform color, and ambiguous structures make the problem challenging [4].…”

Section: Introductionmentioning

confidence: 99%

“…Despite the use of powerful and dedicated video cameras, the cost related to the acquisition material [25] or the actual usefulness of these instruments for dermatologists practising [3] may be the reasons that prevent their wide diffusion to physicians.…”

Section: Introductionmentioning

confidence: 99%

Automatic Segmentation of Dermoscopic Images by Iterative Classification

Zortea

Skrøvseth

Schopf

et al. 2011

International Journal of Biomedical Imaging

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Accurate detection of the borders of skin lesions is a vital first step for computer aided diagnostic systems. This paper presents a novel automatic approach to segmentation of skin lesions that is particularly suitable for analysis of dermoscopic images. Assumptions about the image acquisition, in particular, the approximate location and color, are used to derive an automatic rule to select small seed regions, likely to correspond to samples of skin and the lesion of interest. The seed regions are used as initial training samples, and the lesion segmentation problem is treated as binary classification problem. An iterative hybrid classification strategy, based on a weighted combination of estimated posteriors of a linear and quadratic classifier, is used to update both the automatically selected training samples and the segmentation, increasing reliability and final accuracy, especially for those challenging images, where the contrast between the background skin and lesion is low.

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Can automated dermoscopy image analysis instruments provide added benefit for the dermatologist? A study comparing the results of three systems

Cited by 61 publications

References 20 publications

Computer-Aided Diagnosis of Skin Lesions Using Conventional Digital Photography: A Reliability and Feasibility Study

Computer-Aided Diagnosis of Skin Lesions Using Conventional Digital Photography: A Reliability and Feasibility Study

Current and emerging technologies in melanoma diagnosis: the state of the art

Automatic Segmentation of Dermoscopic Images by Iterative Classification

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