514 citations · 672 across the 7 of their papers we have counts for
7 papers
Nodule detection and generation on chest X-rays: NODE21 Challenge
Ecem Sogancioglu, Bram van Ginneken, Finn Behrendt +16
Pulmonary nodules may be an early manifestation of lung cancer, the leading cause of cancer-related deaths among both men and women. Numerous studies have established that deep lea…
Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning
Alessa Hering, Lasse Hansen, Tony C. W. Mok +50
Image registration is a fundamental medical image analysis task, and a wide variety of approaches have been proposed. However, only a few studies have comprehensively compared medi…
Automated Estimation of Total Lung Volume using Chest Radiographs and Deep Learning
Ecem Sogancioglu, Keelin Murphy, Ernst Th. Scholten +3
Total lung volume is an important quantitative biomarker and is used for the assessment of restrictive lung diseases. In this study, we investigate the performance of several deep-…
Deep Learning for Chest X-ray Analysis: A Survey
Ecem Sogancioglu, Erdi Çallı, Bram van Ginneken +2
Recent advances in deep learning have led to a promising performance in many medical image analysis tasks. As the most commonly performed radiological exam, chest radiographs are a…
Deep Learning with robustness to missing data: A novel approach to the detection of COVID-19
Erdi Çallı, Keelin Murphy, Steef Kurstjens +5
In the context of the current global pandemic and the limitations of the RT-PCR test, we propose a novel deep learning architecture, DFCN (Denoising Fully Connected Network). Since…
FRODO: Free rejection of out-of-distribution samples: application to chest x-ray analysis
Erdi Çallı, Keelin Murphy, Ecem Sogancioglu +1
In this work, we propose a method to reject out-of-distribution samples which can be adapted to any network architecture and requires no additional training data. Publicly availabl…