AIMC Topic: Software

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Open Source Software for Automatic Subregional Assessment of Knee Cartilage Degradation Using Quantitative T2 Relaxometry and Deep Learning.

Cartilage
OBJECTIVE: We evaluated a fully automated femoral cartilage segmentation model for measuring T2 relaxation values and longitudinal changes using multi-echo spin-echo (MESE) magnetic resonance imaging (MRI). We open sourced this model and developed a ...

A meta-analysis on the effectiveness of anthropomorphism in human-robot interaction.

Science robotics
The application of anthropomorphic design features is widely assumed to facilitate human-robot interaction (HRI). However, a considerable number of study results point in the opposite direction. There is currently no comprehensive common ground on th...

Deep learning enables fast and dense single-molecule localization with high accuracy.

Nature methods
Single-molecule localization microscopy (SMLM) has had remarkable success in imaging cellular structures with nanometer resolution, but standard analysis algorithms require sparse emitters, which limits imaging speed and labeling density. Here, we ov...

Foundational Considerations for Artificial Intelligence Using Ophthalmic Images.

Ophthalmology
IMPORTANCE: The development of artificial intelligence (AI) and other machine diagnostic systems, also known as software as a medical device, and its recent introduction into clinical practice requires a deeply rooted foundation in bioethics for cons...

A Redundant Configuration of Four Low-Cost GNSS-RTK Receivers for Reliable Estimation of Vehicular Position and Posture.

Sensors (Basel, Switzerland)
This paper proposes a low-cost sensor system composed of four GNSS-RTK receivers to obtain accurate position and posture estimations for a vehicle in real-time. The four antennas of the receivers are placed so that every three-antennas combination is...

GenTB: A user-friendly genome-based predictor for tuberculosis resistance powered by machine learning.

Genome medicine
BACKGROUND: Multidrug-resistant Mycobacterium tuberculosis (Mtb) is a significant global public health threat. Genotypic resistance prediction from Mtb DNA sequences offers an alternative to laboratory-based drug-susceptibility testing. User-friendly...

KEGG mapping tools for uncovering hidden features in biological data.

Protein science : a publication of the Protein Society
In contrast to artificial intelligence and machine learning approaches, KEGG (https://www.kegg.jp) has relied on human intelligence to develop "models" of biological systems, especially in the form of KEGG pathway maps that are manually created by ca...

Development of a machine learning-based real-time location system to streamline acute endovascular intervention in acute stroke: a proof-of-concept study.

Journal of neurointerventional surgery
BACKGROUND: Delivery of acute stroke endovascular intervention can be challenging because it requires complex coordination of patient and staff across many different locations. In this proof-of-concept paper we (a) examine whether WiFi fingerprinting...

Efficient deep learning architecture with dimension-wise pyramid pooling for nuclei segmentation of histopathology images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Image segmentation remains to be one of the most vital tasks in the area of computer vision and more so in the case of medical image processing. Image segmentation quality is the main metric that is often considered with memory and computation effici...

Robotic sample changers for macromolecular X-ray crystallography and biological small-angle X-ray scattering at the National Synchrotron Light Source II.

Journal of synchrotron radiation
Here we present two robotic sample changers integrated into the experimental stations for the macromolecular crystallography (MX) beamlines AMX and FMX, and the biological small-angle scattering (bioSAXS) beamline LiX. They enable fully automated una...