AIMC Topic: Humans

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MR Image Reconstruction Using Deep Density Priors.

IEEE transactions on medical imaging
Algorithms for magnetic resonance (MR) image reconstruction from undersampled measurements exploit prior information to compensate for missing k-space data. Deep learning (DL) provides a powerful framework for extracting such information from existin...

Fuzzy logic based approaches for gene regulatory network inference.

Artificial intelligence in medicine
The rapid advancements in high-throughput techniques have fueled large-scale production of biological data at very affordable costs. Some of these techniques are microarrays and next-generation sequencing that provide genome level insight of living c...

Ultra-Low-Dose Neck CT With Low-Dose Contrast Material for Preoperative Staging of Thyroid Cancer: Image Quality and Diagnostic Performance.

AJR. American journal of roentgenology
OBJECTIVE: Although CT has been used as a complementary diagnostic method for the preoperative diagnosis of thyroid cancer, it has the shortcomings of substantial radiation exposure and the use of contrast material (CM). The purpose of this article i...

Automated Fetal Head Detection and Circumference Estimation from Free-Hand Ultrasound Sweeps Using Deep Learning in Resource-Limited Countries.

Ultrasound in medicine & biology
Ultrasound imaging remains out of reach for most pregnant women in developing countries because it requires a trained sonographer to acquire and interpret the images. We address this problem by presenting a system that can automatically estimate the ...

Artificial Intelligence for Medical Image Analysis: A Guide for Authors and Reviewers.

AJR. American journal of roentgenology
OBJECTIVE: The purpose of this article is to highlight best practices for writing and reviewing articles on artificial intelligence for medical image analysis.

A hypothetical neural network model for generation of human precision grip.

Neural networks : the official journal of the International Neural Network Society
Humans can stably hold and skillfully manipulate an object by coordinated control of a complex, redundant musculoskeletal system. However, how the human central nervous system actually accomplishes precision grip tasks by coordinated control of finge...

AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy.

Medical physics
PURPOSE: Radiation therapy (RT) is a common treatment option for head and neck (HaN) cancer. An important step involved in RT planning is the delineation of organs-at-risks (OARs) based on HaN computed tomography (CT). However, manually delineating O...

On medical application of neural networks trained with various types of data.

Bioscience trends
Neural networks have garnered attention over the past few years. A neural network is a typical model of machine learning that is used to identify visual patterns. Neural networks are used to solve a wide variety of problems, including image recogniti...

Brain-inspired automated visual object discovery and detection.

Proceedings of the National Academy of Sciences of the United States of America
Despite significant recent progress, machine vision systems lag considerably behind their biological counterparts in performance, scalability, and robustness. A distinctive hallmark of the brain is its ability to automatically discover and model obje...

Deep learning enables cross-modality super-resolution in fluorescence microscopy.

Nature methods
We present deep-learning-enabled super-resolution across different fluorescence microscopy modalities. This data-driven approach does not require numerical modeling of the imaging process or the estimation of a point-spread-function, and is based on ...