Optimal Sound Speed Estimation to Enhance Photoacoustic Image Quality in Breast Microcalcification Detection

2012 ◽  
Author(s):  
Changhan Yoon ◽  
Yangmo Yoo ◽  
Tai-Kyong Song ◽  
Jin Ho Chang
Keyword(s):  
Image Quality ◽  
Sound Speed ◽  
Speed Estimation ◽  
Breast Microcalcification ◽  
Microcalcification Detection

scholarly journals A Computationally Efficient Mean Sound Speed Estimation Method Based on an Evaluation of Focusing Quality for Medical Ultrasound Imaging

Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1368 ◽  
Author(s):  
Lee ◽  
Yoo ◽  
Yoon ◽  
Song
Keyword(s):  
Image Quality ◽  
Sound Speed ◽  
Soft Tissues ◽  
Low Cost ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Speed Estimation ◽  
Sound Speeds ◽  
Hardware Resource

Generally, ultrasound receive beamformers calculate the focusing time delays of fixed sound speeds in human tissue (e.g., 1540 m/s). However, phase distortions occur due to variations of sound speeds in soft tissues, resulting in degradation of image quality. Thus, an optimal estimation of sound speed is required in order to improve image quality. Implementation of real-time sound speed estimation is challenging due to high computational and hardware complexities. In this paper, an optimal sound speed estimation method with a low-cost hardware resource is presented. In the proposed method, the optimal mean sound speed is determined by measuring the amplitude variance of pre-beamformed radio-frequency (RF) data. The proposed method was evaluated with phantom and in vivo experiments, and implemented on Virtex-4 with Xilinx ISE 12.4 using VHDL. Experiment results indicate that the proposed method could estimate the mean optimal sound speed and enhance spatial resolution with a negligible increase in the hardware resource usage.

Ultrasonic Adaptive Sound Speed Estimation for the Diagnosis and Quantification of Hepatic Steatosis: A Pilot Study

2018 ◽  
Vol 40 (06) ◽  
pp. 722-733 ◽  
Author(s):  
Marco Dioguardi Burgio ◽  
Marion Imbault ◽  
Maxime Ronot ◽  
Alex Faccinetto ◽  
Bernard E. Van Beers ◽  
...  
Keyword(s):  
Hepatic Steatosis ◽  
Sound Speed ◽  
Validation Cohort ◽  
Liver Steatosis ◽  
Receiver Operating Curve ◽  
Coefficient Of Determination ◽  
Proton Density ◽  
Speed Estimation ◽  
Training Cohort ◽  
Receiver Operating Curve Analysis

Abstract Purpose To evaluate the ability of a new ultrasound (US) method based on sound speed estimation (SSE) with respect to the detection, quantification, and grading of hepatic steatosis using magnetic resonance (MR) proton density fat fraction (PDFF) as the reference standard and to calculate one US fat index based on the patient’s SSE. Materials and Methods This study received local IRB approval. Written informed consent was obtained from patients. We consecutively included N = 50 patients as the training cohort and a further N = 50 as the validation cohort who underwent both SSE and abdominal MR. Hepatic steatosis was classified according to MR-PDFF cutoffs as: S0 ≤ 6.5 %, S1 6.5 to 16.5 %, S2 16.5 to 22 %, S3 ≥ 22 %. Receiver operating curve analysis was performed to evaluate the diagnostic performance of SSE in the diagnosis of steatosis (S1–S3). Based on the optimal data fit derived from our study, we proposed a correspondence between the MR-PDFF and a US fat index. Coefficient of determination R2 was used to evaluate fit quality and was considered robust when R2 > 0.6. Results The training and validation cohorts presented mean SSE values of 1.570 ± 0.026 and 1.568 ± 0.023 mm/µs for S0 and 1.521 ± 0.031 and 1.514 ± 0.019 mm/µs for S1–S3 (p < 0.01) patients, respectively. An SSE threshold of ≤ 1.537 mm/µs had a sensitivity of 80 % and a specificity of 85.7 % in the diagnosis of steatosis (S1-S3) in the training cohort. Robust correspondence between MR-PDFF and the US fat index was found both for the training (R2 = 0.73) and the validation cohort (R2 = 0.76). Conclusion SSE can be used to detect, quantify and grade liver steatosis and to calculate a US fat index.

scholarly journals Ultrasonic fat fraction quantification using in vivo adaptive sound speed estimation

2018 ◽  
Vol 63 (21) ◽  
pp. 215013 ◽  
Author(s):  
Marion Imbault ◽  
Marco Dioguardi Burgio ◽  
Alex Faccinetto ◽  
Maxime Ronot ◽  
Hanna Bendjador ◽  
...  
Keyword(s):  
Sound Speed ◽  
Speed Estimation ◽  
Fat Fraction

scholarly journals Breast Microcalcification Detection Algorithm Based on Contourlet and ASVM

Algorithms ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 135
Author(s):  
Cai ◽  
Liu ◽  
Luo ◽  
Du ◽  
Tang
Keyword(s):  
Breast Cancer ◽  
Support Vector Machine ◽  
Early Breast Cancer ◽  
Detection Algorithm ◽  
Support Vector ◽  
Important Landmark ◽  
Professional Doctor ◽  
Breast Microcalcification ◽  
Adaptive Support ◽  
Microcalcification Detection

Microcalcification is the most important landmark information for early breast cancer. At present, morphological artificial observation is the main method for clinical diagnosis of such diseases, but it is easy to cause misdiagnosis and missed diagnosis. The present study proposes an algorithm for detecting microcalcification on mammography for early breast cancer. Firstly, the contrast characteristics of mammograms are enhanced by Contourlet transformation and morphology (CTM). Secondly, split the ROI by the improved K-means algorithm. Thirdly, calculate grayscale feature, shape feature, and Histogram of Oriented Gradient (HOG) for the ROI region. The Adaptive support vector machine (ASVM) is used as a tool to classify the rough calcification point and the false calcification point. Under the guidance of a professional doctor, 280 normal images and 120 calcification images were selected for experimentation, of which 210 normal images and 90 images with calcification images were used for training classification. The remaining 100 are used to test the algorithm. It is found that the accuracy of the automatic classification results of the Adaptive support vector machine (ASVM) algorithm reaches 94%, and the experimental results are superior to similar algorithms. The algorithm overcomes various difficulties in microcalcification detection and has great clinical application value.

An evaluation of an in vivo local sound speed estimation technique by the crossed beam method

1990 ◽  
Vol 16 (1) ◽  
pp. 65-72 ◽  
Author(s):  
Masafumi Kondo ◽  
Kinya Takamizawa ◽  
Makoto Hirama ◽  
Kiyoshi Okazaki ◽  
Kazuhiro Iinuma ◽  
...  
Keyword(s):  
Sound Speed ◽  
Speed Estimation ◽  
Estimation Technique ◽  
Beam Method ◽  
Local Sound

Pulse-echo sound speed estimation using second order speckle statistics

2012 ◽  
Author(s):  
Ivan M. Rosado-Mendez ◽  
Kibo Nam ◽  
Ernest L. Madsen ◽  
Timothy J. Hall ◽  
James A. Zagzebski
Keyword(s):  
Sound Speed ◽  
Second Order ◽  
Speed Estimation ◽  
Pulse Echo

Improved sound speed estimation from XBT profiles: a new approach

2016 ◽  
Vol 58 (2) ◽  
pp. 89-92
Author(s):  
P. A. Maheswaran ◽  
◽  
Dominic Ricky Fernandez
Keyword(s):  
Sound Speed ◽  
Speed Estimation ◽  
New Approach
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