Literature DB >> 30703051

Dermoscopy Image Analysis: Overview and Future Directions.

M Emre Celebi, Noel Codella, Allan Halpern.   

Abstract

Dermoscopy is a non-invasive skin imaging technique that permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. While studies on the automated analysis of dermoscopy images date back to the late 1990s, because of various factors (lack of publicly available datasets, open-source software, computational power, etc.), the field progressed rather slowly in its first two decades. With the release of a large public dataset by the International Skin Imaging Collaboration in 2016, development of open-source software for convolutional neural networks, and the availability of inexpensive graphics processing units, dermoscopy image analysis has recently become a very active research field. In this paper, we present a brief overview of this exciting subfield of medical image analysis, primarily focusing on three aspects of it, namely, segmentation, feature extraction, and classification. We then provide future directions for researchers.

Entities:  

Mesh:

Year:  2019        PMID: 30703051     DOI: 10.1109/JBHI.2019.2895803

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  11 in total

1.  MDFNet: application of multimodal fusion method based on skin image and clinical data to skin cancer classification.

Authors:  Qian Chen; Min Li; Chen Chen; Panyun Zhou; Xiaoyi Lv; Cheng Chen
Journal:  J Cancer Res Clin Oncol       Date:  2022-08-03       Impact factor: 4.322

2.  Slit lamp polarized dermoscopy: a cost-effective tool to assess eyelid lesions.

Authors:  Fábio Henrique Luiz Leonardo; Midori Hentona Osaki; Débora Fernandes Biazim; Yara Martins Ortigosa Leonardo; Tammy Hentona Osaki
Journal:  Int Ophthalmol       Date:  2022-09-09       Impact factor: 2.029

3.  Colored Texture Analysis Fuzzy Entropy Methods with a Dermoscopic Application.

Authors:  Mirvana Hilal; Andreia S Gaudêncio; Pedro G Vaz; João Cardoso; Anne Humeau-Heurtier
Journal:  Entropy (Basel)       Date:  2022-06-15       Impact factor: 2.738

4.  Skin Lesion Area Segmentation Using Attention Squeeze U-Net for Embedded Devices.

Authors:  Andrea Pennisi; Domenico D Bloisi; Vincenzo Suriani; Daniele Nardi; Antonio Facchiano; Anna Rita Giampetruzzi
Journal:  J Digit Imaging       Date:  2022-05-03       Impact factor: 4.903

5.  An Effective Skin Cancer Classification Mechanism via Medical Vision Transformer.

Authors:  Suliman Aladhadh; Majed Alsanea; Mohammed Aloraini; Taimoor Khan; Shabana Habib; Muhammad Islam
Journal:  Sensors (Basel)       Date:  2022-05-25       Impact factor: 3.847

6.  Skin Lesion Analysis for Melanoma Detection Using the Novel Deep Learning Model Fuzzy GC-SCNN.

Authors:  Usharani Bhimavarapu; Gopi Battineni
Journal:  Healthcare (Basel)       Date:  2022-05-23

7.  Skin Lesion Segmentation and Multiclass Classification Using Deep Learning Features and Improved Moth Flame Optimization.

Authors:  Muhammad Attique Khan; Muhammad Sharif; Tallha Akram; Robertas Damaševičius; Rytis Maskeliūnas
Journal:  Diagnostics (Basel)       Date:  2021-04-29

8.  Detection of Skin Cancer Based on Skin Lesion Images Using Deep Learning.

Authors:  Walaa Gouda; Najm Us Sama; Ghada Al-Waakid; Mamoona Humayun; Noor Zaman Jhanjhi
Journal:  Healthcare (Basel)       Date:  2022-06-24

9.  PAD-UFES-20: A skin lesion dataset composed of patient data and clinical images collected from smartphones.

Authors:  Andre G C Pacheco; Gustavo R Lima; Amanda S Salomão; Breno Krohling; Igor P Biral; Gabriel G de Angelo; Fábio C R Alves; José G M Esgario; Alana C Simora; Pedro B C Castro; Felipe B Rodrigues; Patricia H L Frasson; Renato A Krohling; Helder Knidel; Maria C S Santos; Rachel B do Espírito Santo; Telma L S G Macedo; Tania R P Canuto; Luíz F S de Barros
Journal:  Data Brief       Date:  2020-08-25

10.  Characterizing Malignant Melanoma Clinically Resembling Seborrheic Keratosis Using Deep Knowledge Transfer.

Authors:  Panagiota Spyridonos; George Gaitanis; Aristidis Likas; Ioannis Bassukas
Journal:  Cancers (Basel)       Date:  2021-12-15       Impact factor: 6.639

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