AIMC Topic: Imaging, Three-Dimensional

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Deep-learning on-chip light-sheet microscopy enabling video-rate volumetric imaging of dynamic biological specimens.

Lab on a chip
Volumetric imaging of dynamic signals in a large, moving, and light-scattering specimen is extremely challenging, owing to the requirement on high spatiotemporal resolution and difficulty in obtaining high-contrast signals. Here we report that throug...

Deformable registration of chest CT images using a 3D convolutional neural network based on unsupervised learning.

Journal of applied clinical medical physics
PURPOSE: The deformable registration of 3D chest computed tomography (CT) images is one of the most important tasks in the field of medical image registration. However, the nonlinear deformation and large-scale displacement of lung tissues caused by ...

A deep-learning approach for direct whole-heart mesh reconstruction.

Medical image analysis
Automated construction of surface geometries of cardiac structures from volumetric medical images is important for a number of clinical applications. While deep-learning-based approaches have demonstrated promising reconstruction precision, these app...

A potential method for sex estimation of human skeletons using deep learning and three-dimensional surface scanning.

International journal of legal medicine
Deep learning based on radiological methods has attracted considerable attention in forensic anthropology because of its superior classification capacities over human experts. However, radiological instruments are limited in their nature of high cost...

EMONAS-Net: Efficient multiobjective neural architecture search using surrogate-assisted evolutionary algorithm for 3D medical image segmentation.

Artificial intelligence in medicine
Deep learning plays a critical role in medical image segmentation. Nevertheless, manually designing a neural network for a specific segmentation problem is a very difficult and time-consuming task due to the massive hyperparameter search space, long ...

Point Cloud Hand-Object Segmentation Using Multimodal Imaging with Thermal and Color Data for Safe Robotic Object Handover.

Sensors (Basel, Switzerland)
This paper presents an application of neural networks operating on multimodal 3D data (3D point cloud, RGB, thermal) to effectively and precisely segment human hands and objects held in hand to realize a safe human-robot object handover. We discuss t...

Robot-assisted stereotactic multiple brain abscesses' puncture: technical case report.

Acta neurochirurgica
We report a case of multiple brain abscesses' puncture, employing the ROSA™ Brain surgical robot (Zimmer Biomet) and the O-arm® O2 Imaging System (Medtronic). A 51-year-old man was diagnosed with multiple supratentorial ring enhancing cystic lesions ...

Computer vision based individual fish identification using skin dot pattern.

Scientific reports
Precision fish farming is an emerging concept in aquaculture research and industry, which combines new technologies and data processing methods to enable data-based decision making in fish farming. The concept is based on the automated monitoring of ...

A siamese network with adaptive gated feature fusion for individual knee OA features grades prediction.

Scientific reports
Grading individual knee osteoarthritis (OA) features is a fine-grained knee OA severity assessment. Existing methods ignore following problems: (1) more accurately located knee joints benefit subsequent grades prediction; (2) they do not consider kne...

Sexing white 2D footprints using convolutional neural networks.

PloS one
Footprints are left, or obtained, in a variety of scenarios from crime scenes to anthropological investigations. Determining the sex of a footprint can be useful in screening such impressions and attempts have been made to do so using single or multi...