The process of multi-organ segmentation plays a vital role in the analysis of medical images and makes great achievements in computer-aided diagnosis. It’s an important process that is a prerequisite for qualitative analysis, diagnosis, monitoring, and treatment of a patient.
Manual segmentation methods takes a lot of time and requires very well-experienced radiologists.AI can detect and segment organs much faster with great accuracies from different kinds of scans
Understand the Use-case under 5 minutes
Article (6 minutes)
“Humans take around 4 minutes to segment the prostate while AI can do it in just 4 seconds”. The article expands on how AI helps radiologists in the organ segmentation process
Read
Video (2 minutes)
Practitioners need to detect outlines and measure specific finding organ, but with old ways, there are some pains according to time and cost, AI makes high impact reducing the time and money in excellent time.
Watch
Get to know more Business and Technical details about the use-case (15-30 minutes)
More detailed introduction covering business and technical aspects
Video (5 minutes)
David Wallis introduces medical image segmentation using deep learning. After explaining the basic concepts and the motivation, he gives three examples of how automated segmentation is being used to solve medical imaging problems
Watch
White Paper
Paper from Siemens Healthineers that touches on multiple aspects related to the topic: it’s importance, what an integrated end-to-end AI system (not just a model), and sharing some concrete examples like Chest Imaging
Read
Article + Customer Testimonial
A good introduction to 3D-Image Segmentation using AI, including a testimonial from the Royal National Orthopedic Hospital. Includes an example for Knee 3D Segmentation from MRI
VisitCase studies, Organizational Aspects, Return on Investment examples
Case Study
See how RSIP Vision leveraged its deep-learning based 3d CT auto-segmentation technology to deliver a customized, fast, robust, production quality solution
ReadMore details on the technical aspects of the use-case
Video (41 minutes)
Explanation for the end to end process of AI based Organ Segmentation: imagery pre-processing, model training, model usage, and comparison to ground truth for accuracy assessment
Watch
Video (11 minutes)
MedSeg is a free medical segmentation tool for CT and MRI data, video presents the basic functions in MedSeg such as windowing, navigation, label selection, and different modes of segmentation.
Watch
Video (4 minutes)
Know how to plug ‘Nvidia AI Assistant Annotation’ package from NVidia Clara into a 3D slicer, video shows ease of using service with an interactive tool like 3D Slicer.
Watch
Technical resources that will help you implement the use-case (notebooks, tutorials..)
Configurable Solution
Publicly available tools from Nvidia (including pre-trained models and configurable solution) for AI medical imaging workflows
Visit
GitHub Repo
toolbox from Microsoft integrated with Azure cloud to train models on medical images, tools support different kinds of models like segmentation, classification, regression, and sequence models.
Visit
Survey Paper
This paper presents a review of deep learning (DL) in multi-organ segmentation. We summarized the latest DL-based methods for medical image segmentation and applications.
VisitGitHub Repo
A self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention.
VisitGitHub Repo
Segmenting 13 different kinds of organs with u-net architecture and some residual connections.
VisitGitHub Repo
Repo provides the code and models files for multi-organ segmentation in abdominal CT using cascaded 3D U-Net models
Visit
Data Sets you can use to build Demos, POCs, or test Algorithms
Comprises 48 patient CT images from the Radiation Therapy Oncology Group (RTOG) (Right Click and Save)
Two databases are used included: Abdominal CT and MRI (T1 and T2 weighted). Each data set in these two databases corresponds to a series of DICOM images belonging to a single patient
Off-the-Shelf Products using AI for Organ Segmentation
Got a Question or a Resource to share with the Community? Please do!
Copyright © 2024 AI Cases. All rights reserved
Session expired
Please log in again. The login page will open in a new tab. After logging in you can close it and return to this page.
