DeepCatch is software that analyzes whole-body CT scans to automatically identify and measure various anatomical structures like skin, muscle, fat, internal organs, and the central nervous system. It produces 3D models and quantitative data to help doctors better understand the patient's body composition and anatomy, aiding clinical decisions by providing accurate volume and proportion measurements.
DeepCatch analyzes CT images and auto-segments anatomical structures (skin, bone, muscle, visceral fat, subcutaneous fat, internal organs and central nervous system). Then, its volume and proportions are calculated and provided with the relevant 3D model. Intended to be used with professional clinical judgement on whole body CT images.
DeepCatch is medical image processing software providing 3D reconstruction, advanced image quality improvement, auto segmentation, and texture analysis. It segments multiple anatomical structures in whole-body CT images, creates 3D visualizations, and calculates volume and proportion data.
Performance testing was conducted with data sets from multiple countries (Korea, France, US) demonstrating over 90% Dice Similarity Coefficient in segmentation accuracy against ground truth, volume and area differences under 10%, and consistency across diverse populations. Comparative tests showed DeepCatch at least equivalent or better than predicate devices MEDIP PRO and Synapse 3D in segmentation and measurement accuracy.
No predicate devices specified
Submission
11/28/2022
FDA Approval
6/16/2023
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