Skin tumours

Khandpur, Sujay; Ramam, M

doi:10.4103/0974-2077.101368

Cited by 16 publications

(21 citation statements)

References 12 publications

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“…However, malignant and benign lesions were equal in proportion in this study. 2 This is similar to findings in Benin, where 51.8% of skin tumours were malignant. 15 The predominance of keratinocytic malignancies and squamous cell carcinomas in particular is in keeping with findings in Lagos, Kano and Zaria.…”

Section: Discussionsupporting

confidence: 78%

Dermatologic neoplasms: a perspective from Makurdi, North Central Nigeria

Ajetunmobi

Dzuachii

2017

Int J Res Dermatol

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Background: Skin cancers are the commonest malignancies in Caucasians but are relatively less common in dark skinned persons. They are strongly linked to ultraviolet exposure, skin melanin content, and immune status.Methods: This study reviewed all histologically diagnosed skin neoplasms at the Federal Medical Centre, Makurdi from January 2012 to December 2016.Results: A total of 84 neoplasms were seen, with 42 (50%) being malignant. Of the malignant lesions, Squamous cell carcinomas were the most frequent (45.2%), followed by melanomas (23.8%). The lower limb was the most frequent site of both benign and malignant neoplasms, while a male to female ratio of 0.88:1 was observed.Conclusions: A relatively high UV radiation intensity, combined with a predominance of outdoor agricultural based activities, alongside chronic ulcerative/inflammatory lesions and a high HIV burden all indicate a need for widespread enlightenment and screening campaigns to prevent occurrence of skin cancers and aid early diagnosis.

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Section: Discussionsupporting

confidence: 78%

Dermatologic neoplasms: a perspective from Makurdi, North Central Nigeria

Ajetunmobi

Dzuachii

2017

Int J Res Dermatol

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“…1 Majority of these tumors are benign. 3 They are basically classified into four groups: tumours with differentiation towards hair follicles, sebaceous glands, eccrine or apocrine glands. These tumours are usually benign, but rarely malignancy can supervene.…”

Section: Introductionmentioning

confidence: 99%

Clinico-pathological study of skin appendageal tumours from northern India

Jain¹,

Jain²,

Singh

et al. 2016

Int J Res Med Sci

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“…Skin lesions develop as a result of proliferation of a single or multiple components of the skin, which ranges from benign lesions to premalignant lesions and aggressive tumors [16]. Since skin lesions progressively invade nearby tissues, there exists a complex correlation between different parts of lesion anatomical structure.…”

Section: Melanoma Benignmentioning

confidence: 99%

Bi-Directional Dermoscopic Feature Learning and Multi-Scale Consistent Decision Fusion for Skin Lesion Segmentation

Wang

Jiang

Ding

et al. 2020

IEEE Trans. on Image Process.

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Accurate segmentation of skin lesion from dermoscopic images is a crucial part of computer-aided diagnosis of melanoma. It is challenging due to the fact that dermoscopic images from different patients have non-negligible lesion variation, which causes difficulties in anatomical structure learning and consistent skin lesion delineation. In this paper, we propose a novel bi-directional dermoscopic feature learning (biDFL) framework to model the complex correlation between skin lesions and their informative context. By controlling feature information passing through two complementary directions, a substantially rich and discriminative feature representation is achieved. Specifically, we place biDFL module on the top of a CNN network to enhance high-level parsing performance. Furthermore, we propose a multi-scale consistent decision fusion (mCDF) that is capable of selectively focusing on the informative decisions generated from multiple classification layers. By analysis of the consistency of the decision at each position, mCDF automatically adjusts the reliability of decisions and thus allows a more insightful skin lesion delineation. The comprehensive experimental results show the effectiveness of the proposed method on skin lesion segmentation, achieving state-of-the-art performance consistently on two publicly available dermoscopic image databases.Index Terms-Skin lesion segmentation, dermoscopic images, bi-directional dermoscopic feature learning, multi-scale consistent decision fusion.

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Skin tumours

Cited by 16 publications

References 12 publications

Dermatologic neoplasms: a perspective from Makurdi, North Central Nigeria

Dermatologic neoplasms: a perspective from Makurdi, North Central Nigeria

Clinico-pathological study of skin appendageal tumours from northern India

Bi-Directional Dermoscopic Feature Learning and Multi-Scale Consistent Decision Fusion for Skin Lesion Segmentation

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