temporal enhanced ultrasound
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Author(s):  
Layan Nahlawi ◽  
Farhad Imani ◽  
Mena Gaed ◽  
Jose A. Gomez ◽  
Madeleine Moussa ◽  
...  

AbstractProstate cancer (PCa) is a common, serious form of cancer in men that is still prevalent despite ongoing developments in diagnostic oncology. Current detection methods lead to high rates of inaccurate diagnosis. We present a method to directly model and exploit temporal aspects of temporal enhanced ultrasound (TeUS) for tissue characterization, which improves malignancy prediction. We employ a probabilistic-temporal framework, namely, hidden Markov models (HMMs), for modeling TeUS data obtained from PCa patients. We distinguish malignant from benign tissue by comparing the respective log-likelihood estimates generated by the HMMs. We analyze 1100 TeUS signals acquired from 12 patients. Our results show improved malignancy identification compared to previous results, demonstrating over 85% accuracy and AUC of 0.95. Incorporating temporal information directly into the models leads to improved tissue differentiation in PCa. We expect our method to generalize and be applied to other types of cancer in which temporal-ultrasound can be recorded.


2020 ◽  
Vol 15 (7) ◽  
pp. 1215-1223
Author(s):  
Alireza Sedghi ◽  
Alireza Mehrtash ◽  
Amoon Jamzad ◽  
Amel Amalou ◽  
William M. Wells ◽  
...  

2019 ◽  
Vol 125 (16) ◽  
pp. 164502
Author(s):  
Si Jia Li ◽  
Jack A. Barnes ◽  
Purang Abolmaesumi ◽  
Parvin Mousavi ◽  
Hans-Peter Loock

2018 ◽  
Vol 37 (12) ◽  
pp. 2695-2703 ◽  
Author(s):  
Shekoofeh Azizi ◽  
Sharareh Bayat ◽  
Pingkun Yan ◽  
Amir Tahmasebi ◽  
Jin Tae Kwak ◽  
...  

Author(s):  
NAVID ZOBEIRY ◽  
SHARAREH BAYAT ◽  
EMRAN ANAS ◽  
PARVIN MOUSAVI ◽  
PURANG ABOLMAESUMI ◽  
...  

2018 ◽  
Vol 65 (8) ◽  
pp. 1798-1809 ◽  
Author(s):  
Layan Nahlawi ◽  
Purang Abolmaesumi ◽  
Hagit Shatkay ◽  
Parvin Mousavi ◽  
Caroline Goncalves ◽  
...  

2018 ◽  
Vol 13 (8) ◽  
pp. 1201-1209 ◽  
Author(s):  
Shekoofeh Azizi ◽  
Nathan Van Woudenberg ◽  
Samira Sojoudi ◽  
Ming Li ◽  
Sheng Xu ◽  
...  

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