Identification of Critical Dermoscopic Features

Award Information
Agency: Department of Health and Human Services
Branch: N/A
Contract: 1R43CA101639-01
Agency Tracking Number: CA101639
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2003
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 (573) 364-0122
Business Contact
Phone: (573) 364-0122
Research Institution
DESCRIPTION (provided by applicant): Malignant melanoma, with an estimated growth in incidence of about 6% per year for decades, causes considerable loss of life. Yet melanoma can be easily cured if detected early. Digital dermoscopy has shown promise for more accurate detection, particularly at an early stage. Recent conferences have highlighted a general agreement on definition of dermoscopic features and moderate agreement on the most useful structural features. Automatic detection of these specific structures that are critical for early diagnosis and are used in various dermoscopic diagnostic algorithms would be desirable. Yet little work has been published on automatic detection of any specific dermoscopic structures. In addition, diagnostic accuracy of digital dermoscopic systems is limited by the failure of systems to properly separate the lesion from the background in a significant number of cases. Although specific colors figure prominently in the definition of the most critical dermoscopic structures, little work has been done on finding the specific regions in the color space where melanoma colors are located, particularly with reference to the surrounding skin. This proposal seeks to improve performance of digital dermoscopy systems by 1) finding borders with greater accuracy 2) developing an algorithm that uses a three-dimensional representation of a probability density function to specify melanoma colors via cluster methods and fuzzy logic techniques 3) identifying critical structural features including brown globules, abrupt border cutoff, granularity, regression, and pigment asymmetry with high accuracy 4) developing a clinical interface for acquisition of images within the clinic 5) developing a web-tool for interactive analysis of images. Key features of the research include dermatopathology confirmation of specific structures and the use of relative color analysis. If successful, specific algorithms would be shared with the growing number of dermatologists using digital dermoscopy. In Phase II, further testing of the algorithms and development of a fast interface would be undertaken. A commercial package combining the software components would be made available for a popular combination digital camera-light head.

* Information listed above is at the time of submission. *

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