Sam. md: Zero-shot medical image segmentation capabilities of the segment anything model
Foundation models have taken over natural language processing and image generation
domains due to the flexibility of prompting. With the recent introduction of the Segment
Anything Model (SAM), this prompt-driven paradigm has entered image segmentation with a
hitherto unexplored abundance of capabilities. The purpose of this paper is to conduct an
initial evaluation of the out-of-the-box zero-shot capabilities of SAM for medical image
segmentation, by evaluating its performance on an abdominal CT organ segmentation task …
domains due to the flexibility of prompting. With the recent introduction of the Segment
Anything Model (SAM), this prompt-driven paradigm has entered image segmentation with a
hitherto unexplored abundance of capabilities. The purpose of this paper is to conduct an
initial evaluation of the out-of-the-box zero-shot capabilities of SAM for medical image
segmentation, by evaluating its performance on an abdominal CT organ segmentation task …
Sam. md: Zero-shot medical image segmentation capabilities of the segment anything model
Foundation models have taken over natural language processing and image generation
domains due to the flexibility of prompting. With the recent introduction of the Segment
Anything Model (SAM), this prompt-driven paradigm has entered image segmentation with a
hitherto unexplored abundance of capabilities. The purpose of this paper is to conduct an
initial evaluation of the out-of-the-box zero-shot capabilities of SAM for medical image
segmentation, by evaluating its performance on an abdominal CT organ segmentation task …
domains due to the flexibility of prompting. With the recent introduction of the Segment
Anything Model (SAM), this prompt-driven paradigm has entered image segmentation with a
hitherto unexplored abundance of capabilities. The purpose of this paper is to conduct an
initial evaluation of the out-of-the-box zero-shot capabilities of SAM for medical image
segmentation, by evaluating its performance on an abdominal CT organ segmentation task …
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