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Semi- automated non- invasive diagnostics method for melanoma differentiation from nevi and pigmented basal cell carcinomas

机译:半自动非侵入性诊断方法,可从黑色素细胞和色素性基底细胞癌中分化出黑色素瘤

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The incidence of skin cancer is still increasing mostly in in industrialized countries with light- skinned people. Late tumour detection is the main reason of the high mortality associated with skin cancer. The accessibility of early diagnostics of skin cancer in Latvia is limited by several factors, such as high cost of dermatology services, long queues on state funded oncologist examinations, as well as inaccessibility of oncologists in the countryside regions - this is an actual clinical problem. The new strategies and guidelines for skin cancer early detection and post-surgical follow-up intend to realize the full body examination (FBE) by primary care physicians (general practitioners, interns) in combination with classical dermoscopy. To implement this approach, a semi- automated method was established. Developed software analyses the combination of 3 optical density images at 540 nm, 650 nm, and 950 nm from pigmented skin malformations and classifies them into three groups- nevi, pigmented basal cell carcinoma or melanoma.
机译:皮肤癌的发病率仍然主要在皮肤白皙的工业化国家中增加。肿瘤的晚期发现是与皮肤癌相关的高死亡率的主要原因。拉脱维亚皮肤癌早期诊断的可及性受到几个因素的限制,例如皮肤病学服务的高昂费用,国家资助的肿瘤科医生检查的排队时间长,以及农村地区的肿瘤科医生无法接触-这是一个实际的临床问题。皮肤癌早期检测和手术后随访的新策略和指南旨在实现初级保健医生(全科医生,实习生)结合经典皮肤镜检查的全身检查(FBE)。为了实施该方法,建立了半自动方法。开发的软件分析了540纳米,650纳米和950纳米来自色素性皮肤畸形的3个光密度图像的组合,并将它们分为三类:痣,色素性基底细胞癌或黑色素瘤。

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