Enhancing Image Segmentation Process in Human Organs Using Python
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V5I2P101Keywords:
Image Segmentation, Medical Imaging, Human Organs, Diagnosis, Treatment PlanningAbstract
This research aims to utilize Python to improve medical imaging of human organs through the use of image segmentation algorithms. With the use of Python libraries like scikit-image, TensorFlow, and OpenCV, different segmentation techniques are investigated in order to define organ boundaries precisely and pinpoint pertinent anatomical features. After segmenting the image, enhancing techniques are applied to improve contrast, clarity, and image quality. In order to improve medical picture interpretability and diagnostic utility and eventually progress patient care and healthcare diagnostics, this study will assess how well segmentation-guided methods for image enhancement work. This work clarifies the possible advantages and difficulties of incorporating segmentation improvement approaches into clinical practice through a thorough examination of Python-based approaches and their future developments in medical imaging
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