Background and Purpose- Discrimination of the stability of intracranial aneurysms is critical for determining the treatment strategy, especially in small aneurysms. This study aims to evaluate the feasibility of applying machine learning for predicti...
Digital reconstruction or tracing of 3D neuron is essential for understanding the brain functions. While existing automatic tracing algorithms work well for the clean neuronal image with a single neuron, they are not robust to trace the neuron surrou...
The ovary is a complex endocrine organ that shows significant structural and functional changes in the female reproductive system over recurrent cycles. There are different types of follicles in the ovarian tissue. The reproductive potential of each ...
Automated identification and localization of vertebrae in spinal computed tomography (CT) imaging is a complicated hybrid task. This task requires detecting and indexing a long sequence in a 3-D image, and both image feature extraction and sequence m...
Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance in many different 2D medical image analysis tasks. In clinical practice, however, a large part of the medical imaging data available is in 3D, e.g, magnetic resonance ima...
Proceedings of the National Academy of Sciences of the United States of America
Jul 8, 2019
Metastasis of solid tumors is a key determinant of cancer patient survival. Targeting micrometastases using nanoparticles could offer a way to stop metastatic tumor growth before it causes excessive patient morbidity. However, nanoparticle delivery t...
Hydrocephalus is a common neurological condition that can have traumatic ramifications and can be lethal without treatment. Nowadays, during therapy radiologists have to spend a vast amount of time assessing the volume of cerebrospinal fluid (CSF) by...
A deeply supervised attention-enabled boosted convolutional neural network (DAB-CNN) is presented as a superior alternative to current state-of-the-art convolutional neural networks (CNNs) for semantic CT segmentation. Spatial attention gates (AGs) w...
Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Jun 24, 2019
PURPOSE: To evaluate the new method to quantitate the running pattern of the vessels in Haller's layer in en face optical coherence tomographic (OCT) images using the new algorithm.
PURPOSE: To study the clinical potential of a deep learning neural network (convolutional neural networks [CNN]) as a supportive tool for detection of intracranial aneurysms from 3D time-of-flight magnetic resonance angiography (TOF-MRA) by comparing...
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