scholarly journals Stochastic Modeling of Temporal Enhanced Ultrasound: Impact of Temporal Properties on Prostate Cancer Characterization

2018 ◽  
Vol 65 (8) ◽  
pp. 1798-1809 ◽  
Author(s):  
Layan Nahlawi ◽  
Purang Abolmaesumi ◽  
Hagit Shatkay ◽  
Parvin Mousavi ◽  
Caroline Goncalves ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Stochastic Modeling ◽  
Temporal Properties ◽  
Temporal Enhanced Ultrasound

Improving detection of prostate cancer foci via information fusion of MRI and temporal enhanced ultrasound

2020 ◽  
Vol 15 (7) ◽  
pp. 1215-1223
Author(s):  
Alireza Sedghi ◽  
Alireza Mehrtash ◽  
Amoon Jamzad ◽  
Amel Amalou ◽  
William M. Wells ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Information Fusion ◽  
Temporal Enhanced Ultrasound

scholarly journals Stochastic Sequential Modeling: Toward Improved Prostate Cancer Diagnosis Through Temporal-Ultrasound

2020 ◽  
Author(s):  
Layan Nahlawi ◽  
Farhad Imani ◽  
Mena Gaed ◽  
Jose A. Gomez ◽  
Madeleine Moussa ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Tissue Characterization ◽  
Markov Models ◽  
Detection Methods ◽  
Benign Tissue ◽  
Temporal Aspects ◽  
Log Likelihood ◽  
Sequential Modeling ◽  
Current Detection ◽  
Temporal Enhanced Ultrasound

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.

scholarly journals Deep Recurrent Neural Networks for Prostate Cancer Detection: Analysis of Temporal Enhanced Ultrasound

2018 ◽  
Vol 37 (12) ◽  
pp. 2695-2703 ◽  
Author(s):  
Shekoofeh Azizi ◽  
Sharareh Bayat ◽  
Pingkun Yan ◽  
Amir Tahmasebi ◽  
Jin Tae Kwak ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Neural Networks ◽  
Cancer Detection ◽  
Recurrent Neural Networks ◽  
Prostate Cancer Detection ◽  
Detection Analysis ◽  
Temporal Enhanced Ultrasound

scholarly journals Models of temporal enhanced ultrasound data for prostate cancer diagnosis: the impact of time-series order

2017 ◽  
Author(s):  
Layan Nahlawi ◽  
Caroline Goncalves ◽  
Farhad Imani ◽  
Mena Gaed ◽  
Jose A. Gomez ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Time Series ◽  
Cancer Diagnosis ◽  
Prostate Cancer Diagnosis ◽  
Series Order ◽  
The Impact ◽  
Temporal Enhanced Ultrasound

Auditory Training to Improve Speech Perception and Self-Efficacy in Aging Adults

2020 ◽  
Vol 63 (4) ◽  
pp. 1270-1281
Author(s):  
Leah Fostick ◽  
Riki Taitelbaum-Swead ◽  
Shulamith Kreitler ◽  
Shelly Zokraut ◽  
Miriam Billig
Keyword(s):  
Speech Perception ◽  
Self Efficacy ◽  
Temporal Order Judgment ◽  
Auditory Training ◽  
Intensity Discrimination ◽  
Training Design ◽  
Auditory Temporal Processing ◽  
Temporal Properties ◽  
Computer Based ◽  
Aging Adults

Purpose Difficulty in understanding spoken speech is a common complaint among aging adults, even when hearing impairment is absent. Correlational studies point to a relationship between age, auditory temporal processing (ATP), and speech perception but cannot demonstrate causality unlike training studies. In the current study, we test (a) the causal relationship between a spatial–temporal ATP task (temporal order judgment [TOJ]) and speech perception among aging adults using a training design and (b) whether improvement in aging adult speech perception is accompanied by improved self-efficacy. Method Eighty-two participants aged 60–83 years were randomly assigned to a group receiving (a) ATP training (TOJ) over 14 days, (b) non-ATP training (intensity discrimination) over 14 days, or (c) no training. Results The data showed that TOJ training elicited improvement in all speech perception tests, which was accompanied by increased self-efficacy. Neither improvement in speech perception nor self-efficacy was evident following non-ATP training or no training. Conclusions There was no generalization of the improvement resulting from TOJ training to intensity discrimination or generalization of improvement resulting from intensity discrimination training to speech perception. These findings imply that the effect of TOJ training on speech perception is specific and such improvement is not simply the product of generally improved auditory perception. It provides support for the idea that temporal properties of speech are indeed crucial for speech perception. Clinically, the findings suggest that aging adults can be trained to improve their speech perception, specifically through computer-based auditory training, and this may improve perceived self-efficacy.

Sigmoidoscopic findings following radiation for prostate cancer

2001 ◽  
Vol 120 (5) ◽  
pp. A284-A284
Author(s):  
T BOLIN ◽  
A KNEEBONE ◽  
T LARSSON
Keyword(s):  
Prostate Cancer

1625: Neuroligin 4 ISOFORM Y: A Novel Marker for Prostate Cancer

2007 ◽  
Vol 177 (4S) ◽  
pp. 538-539
Author(s):  
Joseph F. Pazona ◽  
C. Shad Thaxton ◽  
Neema Navai ◽  
Brian T. Helfand ◽  
Lee C. Zhao ◽  
...  
Keyword(s):  
Prostate Cancer
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