Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Skin Cancer

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

Epidemiology of childhood tuberculosis and factors associated with unsuccessful treatment outcomes in Tigray, Ethiopia: a ten-year retrospective cross sectional study.

BMC public health·2019

Same author

Prevalence and Rates of New Diagnosis and Missed Diagnosis of Diabetes Mellitus among 35-74-year-old Residents in Urban Communities in Southwest China.

Biomedical and environmental sciences : BES·2019

Same author

Insights into the degradation and detoxication mechanisms of aqueous capecitabine in electrochemical oxidation process.

Chemosphere·2019

Same author

Resolving electrical stimulus triggered molecular binding and force modulation upon thrombin-aptamer biointerface.

Journal of colloid and interface science·2019

Same author

Effect of periodic temperature shock on nitrogen removal performance and microbial community structure in plug-flow microaerobic sludge blanket.

Chemosphere·2019

Same author

Central Nervous System Complications after Allogeneic Hematopoietic Stem Cell Transplantation in Children.

Acta haematologica·2019

Search research articles

Related Experiment Video

Updated: May 5, 2026

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging

Published on: May 5, 2011

BDFormer: Boundary-aware dual-decoder transformer for skin lesion segmentation.

Zexuan Ji¹, Yuxuan Ye¹, Xiao Ma¹

¹School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China.

Artificial Intelligence in Medicine

|February 21, 2025

Summary

This study introduces a new transformer model for segmenting skin lesions in dermatoscopic images, improving accuracy by focusing on boundary details and achieving excellent results on multiple datasets.

Keywords:

Dilated boundary-aware Multi-scale aggregation Multi-task distillation Skin lesion segmentation

More Related Videos

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images

Published on: February 18, 2015

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

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

Published on: November 30, 2022

Related Experiment Videos

Last Updated: May 5, 2026

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging

Published on: May 5, 2011

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images

Published on: February 18, 2015

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

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

Published on: November 30, 2022

Area of Science:

Medical image analysis
Computer vision
Artificial intelligence

Background:

Accurate skin lesion segmentation is vital for skin cancer analysis.
Challenges include unclear boundaries, artifacts, hair, and veins.
Transformers show promise but struggle with local details crucial for segmentation.

Purpose of the Study:

To develop an advanced transformer model for precise skin lesion segmentation.
To address the limitation of transformers in capturing local boundary details.
To improve segmentation accuracy by incorporating boundary-aware mechanisms.

Main Methods:

Proposed a boundary-aware dual-decoder transformer with a single encoder and dual decoders.
Introduced shifted window cross-attention and multi-task distillation for inter-task information fusion.
Implemented a multi-scale aggregation strategy and a dilated boundary loss function for enhanced boundary detail.
Utilized a task-wise consistency loss to ensure cross-task coherence.

Main Results:

The proposed model achieved excellent performance on ISIC2018, ISIC2017, and PH2 datasets.
Demonstrated superior segmentation accuracy compared to existing state-of-the-art models.
Effectively handled challenges like unclear boundaries and artifacts.

Conclusions:

The boundary-aware dual-decoder transformer offers a robust solution for skin lesion segmentation.
The novel methods enhance the capture of local details and boundary information.
The model shows significant potential for clinical applications in skin cancer diagnosis.