Download PDF by Okechukwu Felix Erondu: Medical Imaging

By Okechukwu Felix Erondu

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Extra resources for Medical Imaging

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In spite of the huge number of existing methods, the problem of identification in medical images is still challenging, with no general and unique solution and remains an open and promising area in the field of image processing. The growing research in the clinical areas makes the number of objects of interest in medical images to grow constantly, which generates a continuous demand for automatic solutions to aid clinicians. On the other side, fast advances in radiological imaging systems result in increasingly higher volume (3D) images to be processed.

This requires ultrasonic frequencies ranging from 20 MHz to 60 MHz. The increase of ultrasonic frequencies allows a resolution improvement but the wave in the media is attenuated, which limits the applications to superficial exploration. Resolution 3D Ultrasound Image Segmentation: Texture-Based Approaches 3D Ultrasound Image Segmentation: Interactive Texture-BasedInteractive Approaches 453 Fig. 1. Example of a three-dimensional image of the skin obtained with 20 MHz ultrasound scanner (Atys Medical France) provided with high frequencies ultrasound allows to observe the skin perfectly and especially the dermis that has an average thickness ranging from 1 to 2 mm.

Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 2010, pp. 224-307. , Ghita, O. F. (2011). A Novel Model-Based 3D Time Left Ventricular Segmentation Technique. IEEE Trans on Med Imag, vol 30, no 2 (2011), pp. 461-474. -P. & Rasch, M. (2006). Comprehensive cardiovascular image analysis using MR and CT at Siemens Corporate Research. International Journal of Computer Vision, vol. 70, no 2 (2006), pp. 165–178. , Hata, N. G. (2011). Image registration of pre-procedural MRI and intra-procedural CT images to aid CT-guided percutaneous cryoablation of renal tumors.

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