PlumX Metrics
Embed PlumX Metrics

Computer-Aided Diagnosis of Melanoma Subtypes Using Reflectance Confocal Images

Cancers, ISSN: 2072-6694, Vol: 15, Issue: 5
2023
  • 5
    Citations
  • 0
    Usage
  • 15
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    5
  • Captures
    15
  • Mentions
    1
    • Blog Mentions
      1
      • Blog
        1

Article Description

Lentigo maligna (LM) is an early form of pre-invasive melanoma that predominantly affects sun-exposed areas such as the face. LM is highly treatable when identified early but has an ill-defined clinical border and a high rate of recurrence. Atypical intraepidermal melanocytic proliferation (AIMP), also known as atypical melanocytic hyperplasia (AMH), is a histological description that indicates melanocytic proliferation with uncertain malignant potential. Clinically and histologically, AIMP can be difficult to distinguish from LM, and indeed AIMP may, in some cases, progress to LM. The early diagnosis and distinction of LM from AIMP are important since LM requires a definitive treatment. Reflectance confocal microscopy (RCM) is an imaging technique often used to investigate these lesions non-invasively, without biopsy. However, RCM equipment is often not readily available, nor is the associated expertise for RCM image interpretation easy to find. Here, we implemented a machine learning classifier using popular convolutional neural network (CNN) architectures and demonstrated that it could correctly classify lesions between LM and AIMP on biopsy-confirmed RCM image stacks. We identified local z-projection (LZP) as a recent fast approach for projecting a 3D image into 2D while preserving information and achieved high-accuracy machine classification with minimal computational requirements.

Bibliographic Details

Mandal, Ankita; Priyam, Siddhaant; Chan, Hsien Herbert; Gouveia, Bruna Melhoranse; Guitera, Pascale; Song, Yang; Baker, Matthew Arthur Barrington; Vafaee, Fatemeh

MDPI AG

Medicine; Biochemistry, Genetics and Molecular Biology

Provide Feedback

Have ideas for a new metric? Would you like to see something else here?Let us know