Hyalite Sol-Gel Amoeba: A Physiology-Based Biophysical Model for Segmentation and Biotransformation of Medical Images To 3D Solid-State Characterizing Native Tissue Properties for Patient-Specific and Patient-Appropriate Analysis for Surgical Applications

Authors

  • Harjeet Singh Gandhi Hamilton Health Sciences, Ontario

DOI:

https://doi.org/10.24297/ijct.v22i.9228

Keywords:

Sternotomy, Osteochondrotomy, Intensiotaxis, Intensiokinesis, Tissue density, Optical density, Clinical biomechanical engineer, Computer vision, Image segmentation

Abstract

Introduction: The endeavour to improve medical image segmentation techniques for higher analysis in surgical planning and medical therapeutics is far from becoming a standard of care in clinical practice. Hyalite Sol-Gel Amoeba model based on biophysical sciences apart from performing image segmentation is designed to extract real-world tissue densities for patient-specific and patient-appropriate analysis.

Objectives: Amoeba Proteus is a unicellular independent entity, with a nucleus and sol-gel protoplasm enclosed in a membrane. The study presents versatile restructuring anatomy and physiology of the Amoeba Proteus for segmentation of 2D, and 3D medical images based on well-established principles of energy minimization and active contour. It demonstrates how the animalcule glides and advances by throwing pseudopodia driven by phenomenal actin-myosin activity that can segment a region-of-interest, and finally, at the time of apoptosis, its protoplasm and organelles acquire distribution of original image intensities to characterize tissue densities.

Methods: This seminal study following a brief review of computer vision science discusses the relationship between optical density and tissue density, and the theory of sol-gel fluid mechanics. The framework of the HSG-Amoeba is described with the segmentation of various skeletal components of the thoracic cage.

Results: This being a foundational study to describe the concept of the HSG-Amoeba model it requires the development of a mathematical algorithm to demonstrate its worthiness as a tool for surgical applications.

Conclusion: The focus of the study is to present the design and framework of the newly conceived HSG-Amoeba model to segment a medical image and extract tissue densities without altering the original image intensities.

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References

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Published

2022-05-27

How to Cite

Gandhi, H. S. (2022). Hyalite Sol-Gel Amoeba: A Physiology-Based Biophysical Model for Segmentation and Biotransformation of Medical Images To 3D Solid-State Characterizing Native Tissue Properties for Patient-Specific and Patient-Appropriate Analysis for Surgical Applications. INTERNATIONAL JOURNAL OF COMPUTERS &Amp; TECHNOLOGY, 22, 64–85. https://doi.org/10.24297/ijct.v22i.9228

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