ArticleJournal of medical systems2015
A Review of the Quantification and Classification of Pigmented Skin Lesions: From Dedicated to Hand-Held Devices.
Article in Journal of medical systems, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed.
- A Multi-Feature Fusion Framework for Automatic Skin Cancer Diagnostics.Diagnostics (Basel, Switzerland) · 2023Article
- Identifying the role of vision transformer for skin cancer-A scoping review.Frontiers in artificial intelligence · 2023Article
- Digital Natives' Preferences on Mobile Artificial Intelligence Apps for Skin Cancer Diagnostics: Survey Study.JMIR mHealth and uHealth · 2021Article
- An Integrated Platform for Skin Cancer Heterogenous and Multilayered Data Management.Journal of medical systems · 2021Article
- An embedded novel compact feature profile image in speech signal for teledermoscopy system.Health information science and systems · 2020Article
- Melanoma Diagnosis Using Deep Learning and Fuzzy Logic.Diagnostics (Basel, Switzerland) · 2020Article
- Skin Lesion Segmentation in Dermoscopic Images with Combination of YOLO and GrabCut Algorithm.Diagnostics (Basel, Switzerland) · 2019Article
- An Efficient Melanoma Diagnosis Approach Using Integrated HMF Multi-Atlas Map Based Segmentation.Journal of medical systems · 2019Article
- A vessel segmentation method for multi-modality angiographic images based on multi-scale filtering and statistical models.Biomedical engineering online · 2016Article
- Effect of Watermarking on Diagnostic Preservation of Atherosclerotic Ultrasound Video in Stroke Telemedicine.Journal of medical systems · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.