Anatomical segmentation of organs in ultrasound images is essential to many clinical applications, particularly for diagnosis and monitoring.
Dynamic positron emission tomography imaging (dPET) provides temporally resolved images of a tracer enabling a quantitative measure of physiological processes.
Various morphological and functional parameters of peripheral nerves and their vascular supply are indicative of pathological changes due to injury or disease.
Abdominal aortic aneurysm (AAA) is a vascular disease in which a section of the aorta enlarges, weakening its walls and potentially rupturing the vessel.
Medical Ultrasound (US), despite its wide use, is characterized by artifacts and operator dependency.
In this paper we introduce the first reinforcement learning (RL) based robotic navigation method which utilizes ultrasound (US) images as an input.
Automatic surgical phase recognition is a challenging and crucial task with the potential to improve patient safety and become an integral part of intra-operative decision-support systems.
Ranked #4 on Surgical phase recognition on Cholec80
The proposed method displays both promising image reconstruction quality and acquisition frequency when integrated for live ultrasound scanning.
In this paper, we propose a novel interpretation method tailored to histological Whole Slide Image (WSI) processing.
Compared with traditional augmentation methods, and with images synthesized by Generative Adversarial Networks our method not only achieves state-of-the-art performance but also significantly improves the network's robustness.