214 citations · 450 across the 14 of their papers we have counts for
5 papers · 1 filter
Automatically Designing CNN Architectures for Medical Image Segmentation
Aliasghar Mortazi, Ulas Bagci
Deep neural network architectures have traditionally been designed and explored with human expertise in a long-lasting trial-and-error process. This process requires huge amount of…
S4ND: Single-Shot Single-Scale Lung Nodule Detection
Naji Khosravan, Ulas Bagci
The state of the art lung nodule detection studies rely on computationally expensive multi-stage frameworks to detect nodules from CT scans. To address this computational challenge…
Capsules for Object Segmentation
Rodney LaLonde, Ulas Bagci
Convolutional neural networks (CNNs) have shown remarkable results over the last several years for a wide range of computer vision tasks. A new architecture recently introduced by…
A Collaborative Computer Aided Diagnosis (C-CAD) System with Eye-Tracking, Sparse Attentional Model, and Deep Learning
Naji Khosravan, Haydar Celik, Baris Turkbey +3
There are at least two categories of errors in radiology screening that can lead to suboptimal diagnostic decisions and interventions:(i)human fallibility and (ii)complexity of vis…
Semi-supervised multi-task learning for lung cancer diagnosis
Naji Khosravan, Ulas Bagci
Early detection of lung nodules is of great importance in lung cancer screening. Existing research recognizes the critical role played by CAD systems in early detection and diagnos…