Automated Mouse Organ Segmentation: A Deep Learning Based Solution
2018
The analysis of animal cross section images, such as cross sections of laboratory mice, is critical in assessing the effect of
experimental drugssuch as the
biodistributionof candidate compounds in preclinical
drug developmentstage. Tissue distribution of radiolabeled candidate therapeutic compounds can be quantified using techniques like Quantitative Whole-Body Autoradiography (QWBA).QWBA relies, among other aspects, on the accurate segmentation or identification of key organs of interest in the animal cross section image such as the brain, spine, heart, liver and others. We present a deep learning based organ segmentation solution to this problem, using which we can achieve automated organ segmentation with high precision (
dicecoefficient in the 0.83-0.95 range depending on organ) for the key organs of interest.
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