AIMC Topic: Swine

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Feasibility study of three-material decomposition in dual-energy cone-beam CT imaging with deep learning.

Physics in medicine and biology
In this work, a dedicated end-to-end deep convolutional neural network, named as Triple-CBCT, is proposed to demonstrate the feasibility of reconstructing three different material distribution volumes from the dual-energy CBCT projection data.In Trip...

Spectral organ fingerprints for machine learning-based intraoperative tissue classification with hyperspectral imaging in a porcine model.

Scientific reports
Visual discrimination of tissue during surgery can be challenging since different tissues appear similar to the human eye. Hyperspectral imaging (HSI) removes this limitation by associating each pixel with high-dimensional spectral information. While...

Development and Application of Two Inducible Expression Systems for Streptococcus suis.

Microbiology spectrum
Streptococcus suis is an important zoonotic bacterial pathogen posing a threat to the pig industry as well as public health, for which the mechanisms of growth and cell division remain largely unknown. Developing convenient genetic tools that can ach...

Robot-assisted scaffold implantation and two-stage flap raising of the greater omentum for reconstruction of the facial skeleton: Description of a novel technique.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Bone regeneration in the greater omentum is a promising strategy in facial skeleton reconstruction. This feasibility-study aims to perform robot-assisted scaffold implantation and second-stage flap raising.

Epidural anesthesia needle guidance by forward-view endoscopic optical coherence tomography and deep learning.

Scientific reports
Epidural anesthesia requires injection of anesthetic into the epidural space in the spine. Accurate placement of the epidural needle is a major challenge. To address this, we developed a forward-view endoscopic optical coherence tomography (OCT) syst...

Robust deep learning-based semantic organ segmentation in hyperspectral images.

Medical image analysis
Semantic image segmentation is an important prerequisite for context-awareness and autonomous robotics in surgery. The state of the art has focused on conventional RGB video data acquired during minimally invasive surgery, but full-scene semantic seg...

Learning-based autonomous vascular guidewire navigation without human demonstration in the venous system of a porcine liver.

International journal of computer assisted radiology and surgery
PURPOSE: The navigation of endovascular guidewires is a dexterous task where physicians and patients can benefit from automation. Machine learning-based controllers are promising to help master this task. However, human-generated training data are sc...

An image classification deep-learning algorithm for shrapnel detection from ultrasound images.

Scientific reports
Ultrasound imaging is essential for non-invasively diagnosing injuries where advanced diagnostics may not be possible. However, image interpretation remains a challenge as proper expertise may not be available. In response, artificial intelligence al...

Increasing angular sampling through deep learning for stationary cardiac SPECT image reconstruction.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: The GE Discovery NM (DNM) 530c/570c are dedicated cardiac SPECT scanners with 19 detector modules designed for stationary imaging. This study aims to incorporate additional projection angular sampling to improve reconstruction quality. A ...

Telerobotic neurovascular interventions with magnetic manipulation.

Science robotics
Advances in robotic technology have been adopted in various subspecialties of both open and minimally invasive surgery, offering benefits such as enhanced surgical precision and accuracy with reduced fatigue of the surgeon. Despite the advantages, ro...