Dermoscopy for the diagnosis of melanoma: primary care diagnostic technology update

Plüddemann, Annette; Heneghan, Carl; Thompson, Matthew; Wolstenholme, Jane; Price, Christopher P.

doi:10.3399/bjgp11x578142

Cited by 13 publications

(10 citation statements)

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“…The likelihood of featureless melanomas not to be overlooked and minimal excision of benign lesions are increased by the use of dermoscopic monitoring of pigmented lesions. Dermoscopy in routine practice may have major implications in large-scale melanoma screening, with a reduction in the dermatological surgery workload of falsepositive lesions, leading to cost savings, reduced morbidity, and less scarring (Plüddemann et al, 2011). Dermoscopy is a non-invasive and costeffective tool for melanoma diagnosis, which has been shown to be a reliable and sensitive method for detecting early-stage skin cancer and reducing the number of unnecessary excisions (Thomas and Puig, 2017) (Table 1).…”

Section: Advantages Of Dermoscopy In Melanoma Detectionmentioning

confidence: 99%

“…Also, it has its limitation in the case of nail matrix melanoma which has a late onset (Koga, 2017). Table 1: Advantages and disadvantages of dermoscopy (Plüddemann et al, 2011;Koga, 2017;Argenziano et al, 2003) Advantages of dermoscopy Disadvantages of dermoscopy Easy to use Low cost Helps in early detection Requires minimum number of excisions to confirm the diagnosis By using a special lens also lesions are located in particular anatomic sites Modification of luminous intensity and magnification not possible Storage and retrospective analysis of the images is not feasible Requires properly trained dermatologists Fails to diagnose nail matrix melanoma…”

Section: Challenges and Limitations Of Dermoscopymentioning

confidence: 99%

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Appling of evolutionary computing to accelerate for melanoma cancer detection

Al-Marghilnai¹,

Mansour²

2018

Int. j. adv. appl. sci.

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The incidences of malignant melanoma are increasing worldwide. This type of cancer can occur at any age which makes it one of the leading causes of loss of life in young persons. Since this cancer can be visualized easily on the skin of the patients, it is potentially detectable and thus curable at early stages. Nowadays with the help of new developments fully automatic early melanoma detection is really possible. With the advent of dermoscopy, the diagnostic ability to detect melanoma at a very early stage has been increased drastically. Large collections of dermoscopy images of melanomas and benign lesions that are validated by histopathology are now available only because of the adoption of this technology at a global level. A distinction of malignant melanoma from the many benign mimics (that do not require biopsy) is now possible due to the development of advanced technologies in the areas of image processing and machine learning. Not only the earlier detection of melanoma is now possible but also there is a reduction in needless and costly biopsy procedures, only due to these new technologies. However, 3-D feature projection in dermoscopy is a new age method to extract and detect chances of melanoma on the basis of the 3-D reconstruction. The article reviews the impact and importance of computer assisted 3-D imaging.

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Section: Advantages Of Dermoscopy In Melanoma Detectionmentioning

confidence: 99%

Section: Challenges and Limitations Of Dermoscopymentioning

confidence: 99%

Appling of evolutionary computing to accelerate for melanoma cancer detection

Al-Marghilnai¹,

Mansour²

2018

Int. j. adv. appl. sci.

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“…а -клиническое изображение; б -последовательно дерматоскопическое изображение, СИАсканы общего меланина, дермального меланина, распределения гемоглобина и коллагена. злокачественных новообразований кожи (НОК) [5][6][7][8]. Изначально предназначенная для ранней диагностики меланомы кожи СИАскопия вскоре доказала свою высокую чувствительность и специфичность для диагностики других НОК [9].…”

Section: Abstract: Spectrophotometric Intradermal Analysis Siascopyunclassified

Diagnostic capabilities of intradermal spectrophotometric analysis in the differential diagnosis of melanocytic skin lesions

Соколова¹,

Malishevskaya²

2018

Klin. dermatol. venerol.

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“…This in turn, comparing to conventional non-dermoscopic examination, allows physicians to reach a more reliable diagnosis of skin lesions. Thus, recent melanoma guidelines promote the use of dermoscopy in skin cancer screening and diagnosis [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

“…Skin cancer is the most common form of cancer in the US and over 3.5 million cases are diagnosed annually [ 2 ]. The deadliest form of skin cancer is melanoma.…”

Section: Introductionmentioning

confidence: 99%

Density-based parallel skin lesion border detection with webCL

et al. 2015

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BackgroundDermoscopy is a highly effective and noninvasive imaging technique used in diagnosis of melanoma and other pigmented skin lesions. Many aspects of the lesion under consideration are defined in relation to the lesion border. This makes border detection one of the most important steps in dermoscopic image analysis. In current practice, dermatologists often delineate borders through a hand drawn representation based upon visual inspection. Due to the subjective nature of this technique, intra- and inter-observer variations are common. Because of this, the automated assessment of lesion borders in dermoscopic images has become an important area of study.MethodsFast density based skin lesion border detection method has been implemented in parallel with a new parallel technology called WebCL. WebCL utilizes client side computing capabilities to use available hardware resources such as multi cores and GPUs. Developed WebCL-parallel density based skin lesion border detection method runs efficiently from internet browsers.ResultsPrevious research indicates that one of the highest accuracy rates can be achieved using density based clustering techniques for skin lesion border detection. While these algorithms do have unfavorable time complexities, this effect could be mitigated when implemented in parallel. In this study, density based clustering technique for skin lesion border detection is parallelized and redesigned to run very efficiently on the heterogeneous platforms (e.g. tablets, SmartPhones, multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units) by transforming the technique into a series of independent concurrent operations. Heterogeneous computing is adopted to support accessibility, portability and multi-device use in the clinical settings. For this, we used WebCL, an emerging technology that enables a HTML5 Web browser to execute code in parallel for heterogeneous platforms. We depicted WebCL and our parallel algorithm design. In addition, we tested parallel code on 100 dermoscopy images and showed the execution speedups with respect to the serial version. Results indicate that parallel (WebCL) version and serial version of density based lesion border detection methods generate the same accuracy rates for 100 dermoscopy images, in which mean of border error is 6.94%, mean of recall is 76.66%, and mean of precision is 99.29% respectively. Moreover, WebCL version's speedup factor for 100 dermoscopy images' lesion border detection averages around ~491.2.ConclusionsWhen large amount of high resolution dermoscopy images considered in a usual clinical setting along with the critical importance of early detection and diagnosis of melanoma before metastasis, the importance of fast processing dermoscopy images become obvious. In this paper, we introduce WebCL and the use of it for biomedical image processing applications. WebCL is a javascript binding of OpenCL, which takes advantage of GPU computing from a web browser. Therefore, WebCL parallel version of density based skin lesion border de...

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Dermoscopy for the diagnosis of melanoma: primary care diagnostic technology update

Cited by 13 publications

References 14 publications

Appling of evolutionary computing to accelerate for melanoma cancer detection

Appling of evolutionary computing to accelerate for melanoma cancer detection

Diagnostic capabilities of intradermal spectrophotometric analysis in the differential diagnosis of melanocytic skin lesions

Density-based parallel skin lesion border detection with webCL

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