Computationally-efficient wavelet-based characterization of breast tumors using conventional B-mode ultrasound images

2019 ◽  
Author(s):  
Manar Mahmoud ◽  
Muhammad Rushdi ◽  
Iman Ewais ◽  
Eman Hosny ◽  
Hanan Gewefel ◽  
...  
Keyword(s):  
Breast Tumors ◽  
Ultrasound Images ◽  
Computationally Efficient

scholarly journals Wavelet-based computationally-efficient computer-aided characterization of liver steatosis using conventional B-mode ultrasound images

2019 ◽  
Vol 52 ◽  
pp. 84-96 ◽  
Author(s):  
Manar N. Amin ◽  
Muhammad A. Rushdi ◽  
Raghda N. Marzaban ◽  
Ayman Yosry ◽  
Kang Kim ◽  
...  
Keyword(s):  
Liver Steatosis ◽  
Ultrasound Images ◽  
Computationally Efficient ◽  
Computer Aided

Automated Characterization of Atheromatous Plaque in Intravascular Ultrasound Images Using Neuro Fuzzy Classifier

2012 ◽  
Vol 58 (4) ◽  
pp. 425-431 ◽  
Author(s):  
D. Selvathi ◽  
N. Emimal ◽  
Henry Selvaraj
Keyword(s):  
Intravascular Ultrasound ◽  
Human Error ◽  
Human Life ◽  
Classification Performance ◽  
Atheromatous Plaque ◽  
Ultrasound Images ◽  
Fuzzy Classifier ◽  
Neuro Fuzzy ◽  
Calcified Tissues

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%.

Assessing the performance of morphological parameters in distinguishing breast tumors on ultrasound images

2010 ◽  
Vol 32 (1) ◽  
pp. 49-56 ◽  
Author(s):  
André Victor Alvarenga ◽  
Antonio Fernando C. Infantosi ◽  
Wagner Coelho A. Pereira ◽  
Carolina M. Azevedo
Keyword(s):  
Breast Tumors ◽  
Ultrasound Images ◽  
Morphological Parameters

scholarly journals Characterization of N-ethyl-N-nitrosourea-induced malignant and benign breast tumors in rats by using three MR contrast agents

1999 ◽  
Vol 9 (2) ◽  
pp. 177-186 ◽  
Author(s):  
Min-Ying Su ◽  
Zhiheng Wang ◽  
Philip M. Carpenter ◽  
Xiaoyan Lao ◽  
Andreas M�hler ◽  
...  
Keyword(s):  
Contrast Agents ◽  
Breast Tumors ◽  
Mr Contrast Agents ◽  
Benign Breast Tumors

scholarly journals Comprehensive characterization of claudin-low breast tumors reflects the impact of the cell-of-origin on cancer evolution

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Roxane M. Pommier ◽  
Amélien Sanlaville ◽  
Laurie Tonon ◽  
Janice Kielbassa ◽  
Emilie Thomas ◽  
...  
Keyword(s):  
Breast Tumors ◽  
Cancer Evolution ◽  
Cell Of Origin ◽  
The Impact ◽  
Comprehensive Characterization

Abstract S2-04: Comprehensive molecular characterization of invasive lobular breast tumors

2015 ◽  
Author(s):  
Giovanni Ciriello ◽  
Michael L Gatza ◽  
Katherine A Hoadley ◽  
Hailei Zhang ◽  
Suhn K Rhie ◽  
...  
Keyword(s):  
Molecular Characterization ◽  
Breast Tumors

Ultrasound Imaging Characterization of Soft Tissue Dynamics of the Seated Human Body

2020 ◽  
Vol 142 (6) ◽  
Author(s):  
Daisuke Yamada ◽  
Alperen Değirmenci ◽  
Robert D. Howe
Keyword(s):  
Ultrasound Imaging ◽  
Human Body ◽  
Human Subjects ◽  
Excitation Amplitude ◽  
Whole Body ◽  
Ultrasound Images ◽  
Body Dynamics ◽  
Excitation Pattern

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.

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