3 papers
eess.IV2021
Using uncertainty estimation to reduce false positives in liver lesion detection
Ishaan Bhat, Hugo J. Kuijf, Veronika Cheplygina +1
Despite the successes of deep learning techniques at detecting objects in medical images, false positive detections occur which may hinder an accurate diagnosis. We propose a techn…
eess.IV2019
Patient-specific fine-tuning of CNNs for follow-up lesion quantification
Mariëlle J. A. Jansen, Hugo J. Kuijf, Ashis K. Dhara +4
Convolutional neural network (CNN) methods have been proposed to quantify lesions in medical imaging. Commonly more than one imaging examination is available for a patient, but the…
eess.IV2019
Optimal input configuration of dynamic contrast enhanced MRI in convolutional neural networks for liver segmentation
Mariëlle J. A. Jansen, Hugo J. Kuijf, Josien P. W. Pluim
Most MRI liver segmentation methods use a structural 3D scan as input, such as a T1 or T2 weighted scan. Segmentation performance may be improved by utilizing both structural and f…