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A Review of the Quantification and Classification of Pigmented Skin Lesions: From Dedicated to Hand-Held Devices

Overview of attention for article published in Journal of Medical Systems, September 2015
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Title
A Review of the Quantification and Classification of Pigmented Skin Lesions: From Dedicated to Hand-Held Devices
Published in
Journal of Medical Systems, September 2015
DOI 10.1007/s10916-015-0354-8
Pubmed ID
Authors

Mercedes Filho, Zhen Ma, João Manuel R. S. Tavares

Abstract

In recent years, the incidence of skin cancer cases has risen, worldwide, mainly due to the prolonged exposure to harmful ultraviolet radiation. Concurrently, the computer-assisted medical diagnosis of skin cancer has undergone major advances, through an improvement in the instrument and detection technology, and the development of algorithms to process the information. Moreover, because there has been an increased need to store medical data, for monitoring, comparative and assisted-learning purposes, algorithms for data processing and storage have also become more efficient in handling the increase of data. In addition, the potential use of common mobile devices to register high-resolution images of skin lesions has also fueled the need to create real-time processing algorithms that may provide a likelihood for the development of malignancy. This last possibility allows even non-specialists to monitor and follow-up suspected skin cancer cases. In this review, we present the major steps in the pre-processing, processing and post-processing of skin lesion images, with a particular emphasis on the quantification and classification of pigmented skin lesions. We further review and outline the future challenges for the creation of minimum-feature, automated and real-time algorithms for the detection of skin cancer from images acquired via common mobile devices.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
Unknown 62 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 19%
Student > Master 8 13%
Researcher 6 10%
Student > Doctoral Student 5 8%
Student > Bachelor 5 8%
Other 11 17%
Unknown 16 25%
Readers by discipline Count As %
Computer Science 18 29%
Medicine and Dentistry 7 11%
Engineering 7 11%
Nursing and Health Professions 2 3%
Agricultural and Biological Sciences 2 3%
Other 6 10%
Unknown 21 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 October 2015.
All research outputs
#18,428,159
of 22,829,683 outputs
Outputs from Journal of Medical Systems
#808
of 1,149 outputs
Outputs of similar age
#197,363
of 274,283 outputs
Outputs of similar age from Journal of Medical Systems
#25
of 41 outputs
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So far Altmetric has tracked 1,149 research outputs from this source. They receive a mean Attention Score of 4.5. This one is in the 13th percentile – i.e., 13% of its peers scored the same or lower than it.
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We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.