AIMC Topic: Deep Learning

Clear Filters Showing 16131 to 16140 of 28423 articles

Multi-label classification of pelvic organ prolapse using stress magnetic resonance imaging with deep learning.

International urogynecology journal
INTRODUCTION AND HYPOTHESIS: We aimed to develop a deep learning-based multi-label classification model to simultaneously diagnose three types of pelvic organ prolapse using stress magnetic resonance imaging (MRI).

Image Quality and Lesion Detectability of Lower-Dose Abdominopelvic CT Obtained Using Deep Learning Image Reconstruction.

Korean journal of radiology
OBJECTIVE: To evaluate the image quality and lesion detectability of lower-dose CT (LDCT) of the abdomen and pelvis obtained using a deep learning image reconstruction (DLIR) algorithm compared with those of standard-dose CT (SDCT) images.

Circumventing the curse of dimensionality in magnetic resonance fingerprinting through a deep learning approach.

NMR in biomedicine
Magnetic resonance fingerprinting (MRF) is a rapidly developing approach for fast quantitative MRI. A typical drawback of dictionary-based MRF is an explosion of the dictionary size as a function of the number of reconstructed parameters, according t...

Deep learning for image classification in dedicated breast positron emission tomography (dbPET).

Annals of nuclear medicine
OBJECTIVE: This study aimed to investigate and determine the best deep learning (DL) model to predict breast cancer (BC) with dedicated breast positron emission tomography (dbPET) images.

Investigating Simultaneity for Deep Learning-Enhanced Actual Ultra-Low-Dose Amyloid PET/MR Imaging.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Diagnostic-quality amyloid PET images can be created with deep learning using actual ultra-low-dose PET images and simultaneous structural MR imaging. Here, we investigated whether simultaneity is required; if not, MR imaging-...

The adoption of deep learning interpretability techniques on diabetic retinopathy analysis: a review.

Medical & biological engineering & computing
Diabetic retinopathy (DR) is a chronic eye condition that is rapidly growing due to the prevalence of diabetes. There are challenges such as the dearth of ophthalmologists, healthcare resources, and facilities that are unable to provide patients with...

Site-agnostic 3D dose distribution prediction with deep learning neural networks.

Medical physics
PURPOSE: Typically, the current dose prediction models are limited to small amounts of data and require retraining for a specific site, often leading to suboptimal performance. We propose a site-agnostic, three-dimensional dose distribution predictio...

Multiresolution residual deep neural network for improving pelvic CBCT image quality.

Medical physics
PURPOSE: Cone-beam computed tomography (CBCT) is frequently used for accurate image-guided radiation therapy. However, the poor CBCT image quality prevents its further clinical use. Thus, it is important to improve the HU accuracy and structure prese...

Development of a deep learning-based patient-specific target contour prediction model for markerless tumor positioning.

Medical physics
PURPOSE: For pancreatic cancer patients, image guided radiation therapy and real-time tumor tracking (RTTT) techniques can deliver radiation to the target accurately. Currently, for the radiation therapy machine with kV X-ray imaging systems, interna...

Deep Learning for Instrumented Ultrasonic Tracking: From Synthetic Training Data to In Vivo Application.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Instrumented ultrasonic tracking is used to improve needle localization during ultrasound guidance of minimally invasive percutaneous procedures. Here, it is implemented with transmitted ultrasound pulses from a clinical ultrasound imaging probe, whi...