Foundations
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Segmentation
Segmentation
Segmentation is the process by which a physician highlights a brain tumor or anatomical structure. This guides cancer treatment, and it paves the way for visualizing the human body through 3D models. Imagine stacking segmented slices like the ones on the left. The highlighted areas will form a three-dimensional replica of a brain tumor, which is highlighted in green.
A key issue is the time, variation, and human error associated with manual segmentation. Moreover, models using artificial intelligence utilize edge detection and pre-defined rules, posing the risk of faulty detection.
Stochastic segmentation emerges as the next solution for cancer mapping.
The brain contains a myriad of structures, some of which are segmented above.
The Stochastic Method
The Stochastic Method
Random Distribution
Random Distribution
A key differentiator between brain structures is their pigmentation. From a stochastic point of view, structural pigmentation is a random and probabilistic process. Several factors come into play in determining how much or how little a structure's cells are pigmented, including metabolic activity, structural integrity, and quantities of neurotransmitters (the signaling molecules of the brain).
Statistical Testing
Statistical Testing
Since the pigments of anatomical structures are randomly distributed, statistics can be applied to quantify those distributions and differentiate between populations of cells. In medical imaging, this can be observed in grayscale values. Voxels are 3-Dimensional pixels. A grayscale value of zero represents pure black; a grayscale value of 1000 represents pure white. This provides the quantitative basis for our stochastic approach.
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