Med Biol Eng Comput - A hybrid framework for registration of carotid ultrasound images combining iconic and geometric features.

Tópicos

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Resumo

Stroke is the third major cause of death worldwide behind heart disease and cancer. Carotid atherosclerosis is the most frequent cause of ischemic stroke. Early diagnosis of carotid plaque and serial monitoring of its size with the help of imaging modalities can help to prevent the atherosclerotic complications. The main difficulty is inevitable variability of patient's head positions during image acquisitions. The time series registration of carotid images helps to improve the monitoring, characterization, and quantification of the disease by suppressing the global movements of the patient. In this work, a novel hybrid registration technique has been proposed and evaluated for registration of carotid ultrasound images taken at different times. The proposed hybrid method bridges the gap between the feature-based and intensity-based registration methods. The feature-based iterative closest point algorithm is used to provide a coarse registration which is subsequently refined by the intensity-based algorithm. The proposed framework uses rigid transformation model coupled with mutual information (MI) similarity measure and Powell optimizer. For quantitative evaluation, different registration approaches have been compared using four error metrics: visual information fidelity, structural similarity index, correlation coefficient, and MI. Qualitative evaluation has also been done using the visual examination of the registered image pairs.

Resumo Limpo

stroke third major caus death worldwid behind heart diseas cancer carotid atherosclerosi frequent caus ischem stroke earli diagnosi carotid plaqu serial monitor size help imag modal can help prevent atherosclerot complic main difficulti inevit variabl patient head posit imag acquisit time seri registr carotid imag help improv monitor character quantif diseas suppress global movement patient work novel hybrid registr techniqu propos evalu registr carotid ultrasound imag taken differ time propos hybrid method bridg gap featurebas intensitybas registr method featurebas iter closest point algorithm use provid coars registr subsequ refin intensitybas algorithm propos framework use rigid transform model coupl mutual inform mi similar measur powel optim quantit evalu differ registr approach compar use four error metric visual inform fidel structur similar index correl coeffici mi qualit evalu also done use visual examin regist imag pair

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