International challenges have become the de facto standard for comparative assessment of image analysis algorithms. Although segmentation is the most widely investigated medical image processing task, the various challenges have been organized to focus only on specific clinical tasks. We organized the Medical Segmentation Decathlon (MSD)-a biomedical image analysis challenge, in which algorithms compete in a multitude of both tasks and modalities to investigate the hypothesis that a method capable of performing well on multiple tasks will generalize well to a previously unseen task and potentially outperform a custom-designed solution. MSD results confirmed this hypothesis, moreover, MSD winner continued generalizing well to a wide range of other clinical problems for the next two years. Three main conclusions can be drawn from this study: (1) state-of-the-art image segmentation algorithms generalize well when retrained on unseen tasks; (2) consistent algorithmic performance across multiple tasks is a strong surrogate of algorithmic generalizability; (3) the training of accurate AI segmentation models is now commoditized to scientists that are not versed in AI model training.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9287542PMC
http://dx.doi.org/10.1038/s41467-022-30695-9DOI Listing

Publication Analysis

Top Keywords

medical segmentation
8
segmentation decathlon
8
image analysis
8
multiple tasks
8
generalize well
8
tasks
5
decathlon international
4
international challenges
4
challenges facto
4
facto standard
4

Similar Publications

This study aimed to develop a novel reconstruction method for segmental mandibulectomy. In the authors' opinion, reconstruction of the anterior border of the mandibular ramus using a double-arm vascularized fibular flap is important to prevent deformity due to buccal depression and the accumulation of food debris, thereby eliminating masticatory dead space that cannot be filled with prostheses such as implants or dentures. Using conventional reconstruction plates, the reconstructed bone positioned at the anterior border of the mandibular ramus required either fixing with only 1 screw or using 2 plates for stable fixation, making it difficult to position the plates stably.

View Article and Find Full Text PDF

Texture is a significant component used for several applications in content-based image retrieval. Any texture classification method aims to map an anonymously textured input image to one of the existing texture classes. Extensive ranges of methods for labeling image texture were proposed earlier.

View Article and Find Full Text PDF

Background: Deep learning-based segmentation of brain metastases relies on large amounts of fully annotated data by domain experts. Semi-supervised learning offers potential efficient methods to improve model performance without excessive annotation burden.

Purpose: This work tests the viability of semi-supervision for brain metastases segmentation.

View Article and Find Full Text PDF

Osteoarthritis (OA) is heterogeneous and involves structural changes in the whole joint, such as cartilage, meniscus/labrum, ligaments, and tendons, mainly with short T2 relaxation times. Detecting OA before the onset of irreversible changes is crucial for early proactive management and limit growing disease burden. The more recent advanced quantitative imaging techniques and deep learning (DL) algorithms in musculoskeletal imaging have shown great potential for visualizing "pre-OA.

View Article and Find Full Text PDF

In the last decade, the emergence of variant strains of avian orthoreovirus (ARV) has caused an enormous economic impact on the poultry industry across China and other countries. This study aimed to evaluate the molecular evolution of the ARV lineages detected in Chinese commercial broiler farms. Firstly, ARV isolation and identification of commercial broiler arthritis cases from different provinces in China from 2016 to 2021 were conducted.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!