A lognormal multiplicative cascade model for multifractal characterization of skin ultrasound images

Author(s):  
M. Djeddi ◽  
Z. Ouksili ◽  
H. Batatia
2012 ◽  
Vol 58 (4) ◽  
pp. 425-431 ◽  
Author(s):  
D. Selvathi ◽  
N. Emimal ◽  
Henry Selvaraj

Abstract The medical imaging field has grown significantly in recent years and demands high accuracy since it deals with human life. The idea is to reduce human error as much as possible by assisting physicians and radiologists with some automatic techniques. The use of artificial intelligent techniques has shown great potential in this field. Hence, in this paper the neuro fuzzy classifier is applied for the automated characterization of atheromatous plaque to identify the fibrotic, lipidic and calcified tissues in Intravascular Ultrasound images (IVUS) which is designed using sixteen inputs, corresponds to sixteen pixels of instantaneous scanning matrix, one output that tells whether the pixel under consideration is Fibrotic, Lipidic, Calcified or Normal pixel. The classification performance was evaluated in terms of sensitivity, specificity and accuracy and the results confirmed that the proposed system has potential in detecting the respective plaque with the average accuracy of 98.9%.


Spinal Cord ◽  
2020 ◽  
Vol 58 (9) ◽  
pp. 1022-1029
Author(s):  
Nao Tamai ◽  
Takeo Minematsu ◽  
Tomonori Maeda ◽  
Koichi Yabunaka ◽  
Hiromi Sanada

2020 ◽  
Vol 142 (6) ◽  
Author(s):  
Daisuke Yamada ◽  
Alperen Değirmenci ◽  
Robert D. Howe

Abstract To characterize the dynamics of internal soft organs and external anatomical structures, this paper presents a system that combines medical ultrasound imaging with an optical tracker and a vertical exciter that imparts whole-body vibrations on seated subjects. The spatial and temporal accuracy of the system was validated using a phantom with calibrated internal structures, resulting in 0.224 mm maximum root-mean-square (r.m.s.) position error and 13 ms maximum synchronization error between sensors. In addition to the dynamics of the head and sternum, stomach dynamics were characterized by extracting the centroid of the stomach from the ultrasound images. The system was used to characterize the subject-specific body dynamics as well as the intrasubject variabilities caused by excitation pattern (frequency up-sweep, down-sweep, and white noise, 1–10 Hz), excitation amplitude (1 and 2 m/s2 r.m.s.), seat compliance (rigid and soft), and stomach filling (empty and 500 mL water). Human subjects experiments (n = 3) yielded preliminary results for the frequency response of the head, sternum, and stomach. The method presented here provides the first detailed in vivo characterization of internal and external human body dynamics. Tissue dynamics characterized by the system can inform design of vehicle structures and adaptive control of seat and suspension systems, as well as validate finite element models for predicting passenger comfort in the early stages of vehicle design.


2011 ◽  
Vol 38 (4) ◽  
pp. 1820-1831 ◽  
Author(s):  
Hyun-chong Cho ◽  
Lubomir Hadjiiski ◽  
Berkman Sahiner ◽  
Heang-Ping Chan ◽  
Mark Helvie ◽  
...  

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