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Organ Segmentation

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

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1. Get Inspired

Understand the Use-case under 5 minutes

2. Know More

Get to know more Business and Technical details about the use-case (15-30 minutes)

Deeper Intro

More detailed introduction covering business and technical aspects

Business Focused

Case studies, Organizational Aspects, Return on Investment examples

Tech focused

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3. Do

Technical resources that will help you implement the use-case (notebooks, tutorials..)

Data Sets

Data Sets you can use to build Demos, POCs, or test Algorithms

PDDCA

Comprises 48 patient CT images from the Radiation Therapy Oncology Group (RTOG) (Right Click and Save)

CHAOS

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

Solutions

Off-the-Shelf Products using AI for Organ Segmentation

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