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.
Abstract: Medical image segmentation plays a crucial role in various healthcare applications, enabling accurate diagnosis, treatment planning, and disease monitoring. Convolutional Neural Networks ...
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