Efficient Hilbert transform-based alternative to Tofts physiological models for representing MRI dynamic contrast-enhanced images in computer-aided diagnosis of prostate cancer

2015 ◽  
Author(s):  
Kevin M. Boehm ◽  
Shijun Wang ◽  
Karen E. Burtt ◽  
Baris Turkbey ◽  
Samuel Weisenthal ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Hilbert Transform ◽  
Computer Aided Diagnosis ◽  
Physiological Models ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Computer Aided ◽  
Aided Diagnosis

Reproducibility of Dynamic Contrast-enhanced MR Imaging. Part I. Perfusion Characteristics in the Female Pelvis by Using Multiple Computer-aided Diagnosis Perfusion Analysis Solutions

Radiology ◽  
2013 ◽  
Vol 266 (3) ◽  
pp. 801-811 ◽  
Author(s):  
Tobias Heye ◽  
Matthew S. Davenport ◽  
Jeffrey J. Horvath ◽  
Sebastian Feuerlein ◽  
Steven R. Breault ◽  
...  
Keyword(s):  
Mr Imaging ◽  
Computer Aided Diagnosis ◽  
Female Pelvis ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Computer Aided ◽  
Aided Diagnosis

scholarly journals Computer-Aided Diagnosis Improves the Detection of Clinically Significant Prostate Cancer on Multiparametric-MRI: A Multi-Observer Performance Study Involving Inexperienced Readers

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 973
Author(s):  
Valentina Giannini ◽  
Simone Mazzetti ◽  
Giovanni Cappello ◽  
Valeria Maria Doronzio ◽  
Lorenzo Vassallo ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Computer Aided Diagnosis ◽  
Multiparametric Mri ◽  
Performance Study ◽  
Predictive Values ◽  
Cad System ◽  
Computer Aided ◽  
Clinically Significant ◽  
Sensitivity Specificity ◽  
Aided Diagnosis

Recently, Computer Aided Diagnosis (CAD) systems have been proposed to help radiologists in detecting and characterizing Prostate Cancer (PCa). However, few studies evaluated the performances of these systems in a clinical setting, especially when used by non-experienced readers. The main aim of this study is to assess the diagnostic performance of non-experienced readers when reporting assisted by the likelihood map generated by a CAD system, and to compare the results with the unassisted interpretation. Three resident radiologists were asked to review multiparametric-MRI of patients with and without PCa, both unassisted and assisted by a CAD system. In both reading sessions, residents recorded all positive cases, and sensitivity, specificity, negative and positive predictive values were computed and compared. The dataset comprised 90 patients (45 with at least one clinically significant biopsy-confirmed PCa). Sensitivity significantly increased in the CAD assisted mode for patients with at least one clinically significant lesion (GS > 6) (68.7% vs. 78.1%, p = 0.018). Overall specificity was not statistically different between unassisted and assisted sessions (94.8% vs. 89.6, p = 0.072). The use of the CAD system significantly increases the per-patient sensitivity of inexperienced readers in the detection of clinically significant PCa, without negatively affecting specificity, while significantly reducing overall reporting time.

scholarly journals Classification of Breast Masses Using a Computer-Aided Diagnosis Scheme of Contrast Enhanced Digital Mammograms

2018 ◽  
Vol 46 (9) ◽  
pp. 1419-1431 ◽  
Author(s):  
Gopichandh Danala ◽  
Bhavika Patel ◽  
Faranak Aghaei ◽  
Morteza Heidari ◽  
Jing Li ◽  
...  
Keyword(s):  
Computer Aided Diagnosis ◽  
Breast Masses ◽  
Contrast Enhanced ◽  
Computer Aided ◽  
Aided Diagnosis
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