AIMC Topic: Imaging, Three-Dimensional

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Incidental cerebral aneurysms detected by a computer-assisted detection system based on artificial intelligence: A case series.

Medicine
RATIONALE: Computer-assisted detection (CAD) systems based on artificial intelligence (AI) using convolutional neural network (CNN) have been successfully used for the diagnosis of unruptured cerebral aneurysms in experimental situations. However, it...

Toward accurate quantitative photoacoustic imaging: learning vascular blood oxygen saturation in three dimensions.

Journal of biomedical optics
SIGNIFICANCE: Two-dimensional (2-D) fully convolutional neural networks have been shown capable of producing maps of sO2 from 2-D simulated images of simple tissue models. However, their potential to produce accurate estimates in vivo is uncertain as...

Accurate Screening of COVID-19 Using Attention-Based Deep 3D Multiple Instance Learning.

IEEE transactions on medical imaging
Automated Screening of COVID-19 from chest CT is of emergency and importance during the outbreak of SARS-CoV-2 worldwide in 2020. However, accurate screening of COVID-19 is still a massive challenge due to the spatial complexity of 3D volumes, the la...

Prior-Attention Residual Learning for More Discriminative COVID-19 Screening in CT Images.

IEEE transactions on medical imaging
We propose a conceptually simple framework for fast COVID-19 screening in 3D chest CT images. The framework can efficiently predict whether or not a CT scan contains pneumonia while simultaneously identifying pneumonia types between COVID-19 and Inte...

A deep learning oriented method for automated 3D reconstruction of carotid arterial trees from MR imaging.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The scope of this paper is to present a new carotid vessel segmentation algorithm implementing the U-net based convolutional neural network architecture. With carotid atherosclerosis being the major cause of stroke in Europe, new methods that can pro...

Deep Learning based Quantification of Ovary and Follicles using 3D Transvaginal Ultrasound in Assisted Reproduction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Quantification of ovarian and follicular volume and follicle count are performed in clinical practice for diagnosis and management in assisted reproduction. Ovarian volume and Antral Follicle Count (AFC) are typically tracked over the ovulation cycle...

Malocclusion Classification on 3D Cone-Beam CT Craniofacial Images Using Multi-Channel Deep Learning Models.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Analyzing and interpreting cone-beam computed tomography (CBCT) images is a complicated and often time-consuming process. In this study, we present two different architectures of multi-channel deep learning (DL) models: "Ensemble" and "Synchronized m...

Deep-learning-based human motion tracking for rehabilitation applications using 3D image features.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Motion rehabilitation is increasingly required owing to an aging population and suffering of stroke, which means human motion analysis must be valued. Based on the concept mentioned above, a deep-learning-based system is proposed to track human motio...

Frameless ROSA® Robot-Assisted Lead Implantation for Deep Brain Stimulation: Technique and Accuracy.

Operative neurosurgery (Hagerstown, Md.)
BACKGROUND: Frameless robotic-assisted surgery is an innovative technique for deep brain stimulation (DBS) that has not been assessed in a large cohort of patients.