Name
Affiliation
Papers
PATRICK C. BRENNAN
university of sydney
37
Collaborators
Citations 
PageRank 
102
4
12.71
Referers 
Referees 
References 
20
68
16
Search Limit
100102
Title
Citations
PageRank
Year
Investigating The Potential Of A Gist-Sensitive Computer-Aided Detection Tool00.342020
Effect Of Time Of Day On Radiology Image Interpretations00.342020
Computer-Assisted Nuclear Atypia Scoring of Breast Cancer: a Preliminary Study.00.342019
Can a Machine Learn from Radiologists' Visual Search Behaviour and Their Interpretation of Mammograms-a Deep-Learning Study.00.342019
Comparing senior residents performance to radiologists in lung cancer detection.00.342019
Estimating latent reader-performance variability using the Obuchowski-Rockette method.00.342019
Does the strength of the gist signal predict the difficulty of breast cancer detection in usual presentation and reporting mechanisms?00.342019
BI-RADS density categorization using deep neural networks.00.342019
A deep (learning) dive into visual search behaviour of breast radiologists.00.342018
Knowledge and practice of computed tomography exposure parameters amongst radiographers in Jordan.00.342018
Breast lesion shape and margin evaluation: BI-RADS based metrics understate radiologists' actual levels of agreement.00.342018
Detection Of The Abnormal Gist In The Prior Mammograms Even With No Overt Sign Of Breast Cancer00.342018
High-Resolution X-ray Phase-Contrast 3D Imaging of Breast Tissue Specimens as a Possible Adjunct to Histopathology.00.342018
Characteristics of the group of radiologists that benefits the most using Breast Screen Reader Assessment Strategy (BREAST).00.342018
A Framework For Distinguishing Benign From Malignant Breast Histopathological Images Using Deep Residual Networks00.342018
Towards Clinic-Friendly Solutions For Patient Trials In Breast Cancer Phase Contrast Imaging00.342018
Does Expectation of Abnormality Affect the Search Pattern of Radiologists When Looking for Pulmonary Nodules?10.352017
Determining local and contextual features describing appearance of difficult to identify mitotic figures.00.342017
Predicting radiologists' true and false positive decisions in reading mammograms by using gaze parameters and image-based features.00.342016
Breast Asymmetry, Distortion and Density Are Key Factors for False Positive Decisions.00.342016
A Pilot Study on Radiation Dose from Combined Mammography Screening in Australia.00.342016
The classification of normal screening mammograms.00.342016
Lower Recall Rates Reduced Readers' Sensitivity in Screening Mammography.00.342016
Quantra reproduces BI-RADS assessment on a two-point scale.00.342016
The impact of radiology expertise upon the localization of subtle pulmonary lesions.10.342016
Investigating the link between the radiological experience and the allocation of an 'equivocal finding'.00.342016
The effectiveness of the cranio-caudal mammogram projection among radiologists.00.342016
Varying performance in mammographic interpretation across two countries: Do results indicate reader or population variances?00.342016
An Investigation into the Consistency in Mammographic Density Identification by Radiologists: Effect of Radiologist Expertise and Mammographic Appearance00.342015
BREAST: A Novel Strategy to Improve the Detection of Breast Cancer.00.342014
Mammographic Density Effect on Readers' Performance and Visual Search Pattern.00.342014
Mammography: Radiologist and Image Characteristics That Determine the Accuracy of Breast Cancer Diagnosis.00.342014
Understanding the Role of Correct Lesion Assessment in Radiologists' Reporting of Breast Cancer.00.342014
Optimization of Computed Tomography Protocols: Limitations of a Methodology Employing a Phantom with Location-Known Opacities.00.342013
Trend of Contrast Detection Threshold with and without Localization.00.342013
Breast Screen New South Wales Generally Demonstrates Good Radiologic Viewing Conditions.00.342013
Verification of DICOM GSDF in Complex Backgrounds.20.522012