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

You might also read

Related Articles

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

Sort by

Same author

Exercise modulates food reward: neurobiological mechanisms and implications for weight management.

Frontiers in nutrition·2026

Same author

Antibody-drug conjugates in breast cancer: from mechanism to revolutionizing clinical practice.

Molecular cancer·2026

Same author

A Genetically Encoded Calcium Ion Biosensor with an Exceptionally Large Ratiometric Response.

ACS sensors·2026

Same author

Forecasting Alzheimer's disease progression via identity-preserved denoising diffusion generative adversarial network.

NPJ digital medicine·2026

Same author

CAMP: A Context-Aware, Multimodal, and Privacy-Preserving Pedestrian Trajectory Prediction Framework.

Journal of imaging·2026

Same author

Edible Fungus Compound Cordycepin Protects Against Acetaminophen-Induced Liver Injury.

Journal of clinical laboratory analysis·2026

Same journal

ECG arrhythmia classification via wavelet-driven feature extraction and swarm-optimised gradient boosting.

Computers in biology and medicine·2026

Same journal

Electro-osmotic metachronal cilia transport of viscoelastic blood infused with penta-hybrid nanoparticles in an oviduct: Analytical and neural network modeling.

Computers in biology and medicine·2026

Same journal

sEEGnal: an automated EEG preprocessing pipeline evaluated against expert-driven preprocessing.

Computers in biology and medicine·2026

Same journal

Corrigendum to "Integrating experimental biology, computational methods, and artificial Intelligence in anticancer drug discovery: Bridging the translational Gap" [Comput. Biol. Med. 213 (2026) 111832].

Computers in biology and medicine·2026

Same journal

Organ dose optimization for a point-of-care forearm X-ray photon-counting CT.

Computers in biology and medicine·2026

Same journal

Physics-guided transformation of breathomic feature spaces into disease-specific representations for respiratory disease classification.

Computers in biology and medicine·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Aug 14, 2025

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

Multi-task deep learning for medical image computing and analysis: A review.

Yan Zhao¹, Xiuying Wang², Tongtong Che¹

¹Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100083, China.

Computers in Biology and Medicine

|January 12, 2023

Summary

This summary is machine-generated.

Multi-task deep learning (MTDL) enhances medical image analysis by performing multiple tasks simultaneously. This review highlights MTDL applications, architectures, and challenges in medical imaging, showing promising but improvable performance.

Keywords:

Deep learning Medical image analysis Medical image application Multi-task learning Survey

More Related Videos

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

Related Experiment Videos

Last Updated: Aug 14, 2025

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

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

Area of Science:

Artificial Intelligence
Medical Image Computing
Deep Learning

Background:

Conventional deep learning models are task-specific.
Multi-task deep learning (MTDL) simultaneously addresses multiple related tasks, improving performance, generalizability, and efficiency.
MTDL leverages inherent correlations between tasks for mutual benefit.

Purpose of the Study:

To review advanced applications of MTDL in medical image computing and analysis.
To summarize popular MTDL network architectures.
To identify challenges and future trends in MTDL for medical imaging.

Main Methods:

Summarized four popular MTDL network architectures: cascaded, parallel, interacted, and hybrid.
Reviewed representative MTDL-based networks across eight medical application areas (brain, eye, chest, cardiac, abdomen, musculoskeletal, pathology, and others).

Main Results:

MTDL demonstrates flourishing performance in many medical image analysis tasks.
Identified performance gaps in specific MTDL applications.
Example: 2018 Ischemic Stroke Lesion Segmentation challenge showed top dice score of 0.51 and recall of 0.55 with cascaded MTDL.

Conclusions:

MTDL shows significant promise and outstanding performance in medical image analysis.
Further research is needed to address performance gaps and enhance current MTDL models.
Future trends point towards continued advancements in MTDL for diverse medical imaging applications.