Abstract: Medical image segmentation is essential for computer-assisted diagnosis since it allows exact extraction of anatomical structures from CT/MRI data. Traditional approaches struggle to handle ...

Threshold-based segmentation by selecting a target color vector in one of six color spaces (RGB, HSV, CIELAB, CIEXYZ, YCbCr or YIQ (NTSC)) and isolating pixels within a user-specified tolerance.

Abstract: The success of deep learning in 3D medical image segmentation hinges on training with a large dataset of fully annotated 3D volumes, which are difficult and time-consuming to acquire.