Literature DB >> 29994234

A Survey of Feature Extraction in Dermoscopy Image Analysis of Skin Cancer.

Catarina Barata, M Emre Celebi, Jorge S Marques.   

Abstract

Dermoscopy image analysis (DIA) is a growing field, with works being published every week. This makes it difficult not only to keep track of all the contributions, but also for new researchers to identify relevant information and new directions to be explored. Several surveys have been written in the past decade, but these tend to cover all of the steps of a CAD system, which can be overwhelming. Moreover, in these works, each of the steps is briefly discussed due to lack of space. Among the different blocks of the CAD system, the most relevant is the one devoted to feature extraction. This is also the block where existing works exhibit the most variability. Therefore, we believe that it is important to review the state-of-the-art on this matter. This work thoroughly explores the several types of features that have been used in DIA. A discussion on their relevance and limitations, as well as suggestions for future research are provided.

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Year:  2018        PMID: 29994234     DOI: 10.1109/JBHI.2018.2845939

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


  6 in total

1.  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

2.  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

3.  Classification of skin lesions using transfer learning and augmentation with Alex-net.

Authors:  Khalid M Hosny; Mohamed A Kassem; Mohamed M Foaud
Journal:  PLoS One       Date:  2019-05-21       Impact factor: 3.240

4.  Melanoma Classification Using a Novel Deep Convolutional Neural Network with Dermoscopic Images.

Authors:  Ranpreet Kaur; Hamid GholamHosseini; Roopak Sinha; Maria Lindén
Journal:  Sensors (Basel)       Date:  2022-02-02       Impact factor: 3.576

5.  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

6.  Clinically Inspired Skin Lesion Classification through the Detection of Dermoscopic Criteria for Basal Cell Carcinoma.

Authors:  Carmen Serrano; Manuel Lazo; Amalia Serrano; Tomás Toledo-Pastrana; Rubén Barros-Tornay; Begoña Acha
Journal:  J Imaging       Date:  2022-07-12
  6 in total

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