WSEAS Transactions on Biology and Biomedicine
Print ISSN: 1109-9518 , E-ISSN: 2224-2902
Volume 21, 2024
Custom Automatic Segmentation Models for Medicine and Biology based on FastSAM
Authors: , , , , , , , ,
Abstract: FastSAM, a public image segmentation model trained on everyday images, is used to achieve a customizable and state-of-the-art segmentation model minimizing the training in two completely different scenarios. In one example we consider macroscopic X-ray images of the knee area. In the second example, images were acquired by microscopy of the volumetric zebrafish embryo retina with a much smaller spatial scale. In both cases, we analyze the minimum set of images required to segmentate keeping the state-of-the-art standards. The effect of filters on the pictures and the specificities of considering a 3D volume for the retina images are also analyzed.
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Keywords: Automatic segmentation, FastSAM, X-ray images, microscopy images, Low-Resource Friendly, Generalizable Approach
Pages: 373-384
DOI: 10.37394/23208.2024.21.38