Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Skin Cancer01:30

Skin Cancer

Skin cancer is a type of cancer that occurs when there is an abnormal growth of skin cells, usually triggered by damage to the DNA within the skin cells. It is primarily caused by exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds. Skin cancer is the most common type of cancer worldwide, and its incidence continues to rise.
Basal Cell Carcinoma (BCC): BCC is the most common type of skin cancer, accounting for about 80% of cases. It typically develops in...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Why physicians underuse patient-reported outcomes in atopic dermatitis and chronic urticaria - Insights from the UCARE/ADCARE PROMUSE study.

The World Allergy Organization journal·2026
Same author

The Impact of Hidradenitis Suppurativa on Sexual Function: A Multicentered Cross-Sectional Study.

International journal of dermatology·2026
Same author

The definition of response and inadequate response to topical corticosteroid treatment in atopic dermatitis and related skin inflammatory diseases: A GA<sup>2</sup>LEN ADCARE statement paper.

The World Allergy Organization journal·2026
Same author

Factors Associated with Symptomatic Dermographism: Findings from the UCARE PREVALENCE-D Study.

American journal of clinical dermatology·2026
Same author

A Review of U-Net Based Deep Learning Frameworks for MRI-Based Brain Tumor Segmentation.

Diagnostics (Basel, Switzerland)·2026
Same author

Family quality-of-life burden in chronic spontaneous urticaria: A multicentre study.

Journal of the European Academy of Dermatology and Venereology : JEADV·2026

Related Experiment Video

Updated: Jul 6, 2026

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging
06:08

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging

Published on: May 5, 2011

16.7K

YOLOSAMIC: A Hybrid Approach to Skin Cancer Segmentation with the Segment Anything Model and YOLOv8.

Sevda Gül1, Gökçen Cetinel2, Bekir Murat Aydin2

  • 1Department of Electronics and Automation, Adapazarı Vocational School, Sakarya University, 54050 Serdivan, Türkiye.

Diagnostics (Basel, Switzerland)
|February 26, 2025
PubMed
Summary

YOLOSAMIC, an automated skin lesion segmentation tool, accurately identifies and segments cancerous moles using YOLOv8 and Segment Anything Model (SAM)-Box. This AI-powered system aids dermatologists in early skin cancer detection.

Keywords:
SAM-BoxYOLOv8artificial intelligenceobject detectionskin lesion segmentation

More Related Videos

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment
10:39

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

Published on: May 24, 2022

2.3K
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.6K

Related Experiment Videos

Last Updated: Jul 6, 2026

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging
06:08

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging

Published on: May 5, 2011

16.7K
A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment
10:39

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

Published on: May 24, 2022

2.3K
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.6K

Area of Science:

  • Dermatology and Artificial Intelligence
  • Medical Image Analysis

Background:

  • Rising global skin cancer incidence necessitates advanced diagnostic tools.
  • Early detection of skin cancer is crucial for effective intervention.
  • Current diagnostic methods require improvement in accuracy and efficiency.

Purpose of the Study:

  • To introduce YOLOSAMIC, a fully automated segmentation framework for skin lesions.
  • To integrate YOLOv8 for lesion detection and Segment Anything Model (SAM)-Box for precise segmentation.
  • To develop a reliable system for complex skin lesion analysis without manual intervention.

Main Methods:

  • A hybrid dataset of 4228 dermoscopy images (public and private) was utilized.
  • YOLOv8 performed bounding box detection for lesion localization.
  • SAM-Box refined segmentation, with evaluation across four scenarios and an ablation study.

Main Results:

  • YOLOSAMIC achieved high segmentation accuracy: Dice scores of 0.9399 (public) and 0.8990 (hybrid).
  • Jaccard scores reached 0.9112 (public) and 0.8445 (hybrid).
  • The framework demonstrated robustness and effectiveness on diverse datasets.

Conclusions:

  • YOLOSAMIC offers a robust, automated solution for skin lesion segmentation.
  • The integration of YOLOv8 and SAM-Box enhances segmentation precision.
  • This framework serves as a valuable AI-driven decision-support tool for dermatologists.