54 citations · 66 across the 7 of their papers we have counts for
7 papers
Deep Learning Fetal Ultrasound Video Model Match Human Observers in Biometric Measurements
Szymon Płotka, Adam Klasa, Aneta Lisowska +4
Objective. This work investigates the use of deep convolutional neural networks (CNN) to automatically perform measurements of fetal body parts, including head circumference, bipar…
Artificial Intelligence in PET: an Industry Perspective
Arkadiusz Sitek, Sangtae Ahn, Evren Asma +6
Artificial intelligence (AI) has significant potential to positively impact and advance medical imaging, including positron emission tomography (PET) imaging applications. AI has t…
Pneumothorax and chest tube classification on chest x-rays for detection of missed pneumothorax
Benedikt Graf, Arkadiusz Sitek, Amin Katouzian +5
Chest x-ray imaging is widely used for the diagnosis of pneumothorax and there has been significant interest in developing automated methods to assist in image interpretation. We p…
Deep Learning based detection of Acute Aortic Syndrome in contrast CT images
Manikanta Srikar Yellapragada, Yiting Xie, Benedikt Graf +3
Acute aortic syndrome (AAS) is a group of life threatening conditions of the aorta. We have developed an end-to-end automatic approach to detect AAS in computed tomography (CT) ima…
Human Gist Processing Augments Deep Learning Breast Cancer Risk Assessment
Skylar W. Wurster, Arkadiusz Sitek, Jian Chen +3
Radiologists can classify a mammogram as normal or abnormal at better than chance levels after less than a second's exposure to the images. In this work, we combine these radiologi…
Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis
Xiang Li, Aoxiao Zhong, Ming Lin +6
Tissue characterization has long been an important component of Computer Aided Diagnosis (CAD) systems for automatic lesion detection and further clinical planning. Motivated by th…
Learning the Sparse and Low Rank PARAFAC Decomposition via the Elastic Net
Songting Shi, Xiang Li, Arkadiusz Sitek +1
In this article, we derive a Bayesian model to learning the sparse and low rank PARAFAC decomposition for the observed tensor with missing values via the elastic net, with property…