Latest AI and machine learning research in surgery for healthcare professionals.
Deep neural networks have demonstrated promising potential for the field of medical image reconstruction, successfully generating high quality images for CT, PET and MRI. In this work, an MRI reconstruction algorithm, which is referred to as quantitative susceptibility mapping (QSM), has been developed using a deep neural network in order to perform dipole deconvolution, which restores magnetic su...
Surgical guidance and decision making could be improved with accurate and real-time measurement of intra-operative data including shape and spectral information of the tissue surface. In this work, a dual-modality endoscopic system has been proposed to enable tissue surface shape reconstruction and hyperspectral imaging (HSI). This system centers around a probe comprised of an incoherent fiber bun...
The notion that robotic crop pollination will solve the decline in pollinators has gained wide popularity recently (Fig. 1), and in March 2018 Walmart...
The breast stromal microenvironment is a pivotal factor in breast cancer development, growth and metastases. Although pathologists often detect morpho...
Laparoscopic complete mesocolic excision (CME) for transverse colon cancer is technically challenging. Robotic technology has been developed to reduc...
Determination of the material properties of soft tissue is a growing area of interest that aids in the development of new surgical tools and surgical ...
BACKGROUND: Esophageal schwannomas are extremely rare, with few cases reported in the literature. Traditionally, resection of esophageal schwannoma is...
Random forests are a popular nonparametric tree ensemble procedure with broad applications to data analysis. While its widespread popularity stems fro...
Robots were introduced in rehabilitation in the 90s to meet different needs, that is, reducing the physical effort of therapists. This work consists o...
Over the past 30 years, the application of robotics in the field of neurotology has grown. Robots are able to perform increasingly complex tasks with ...
To realize the full potential of deep learning for medical imaging, large annotated datasets are required for training. Such datasets are difficult to...
Targeted prostate biopsy, incorporating multi-parametric magnetic resonance imaging (mp-MRI) and its registration with ultrasound, is currently the st...
The impact of direct oral anticoagulants (DOACs) on laboratory assays used for thrombophilia testing (e.g., antithrombin, protein S, protein C, lupus ...
Soft tissue deformation modelling forms the basis of development of surgical simulation, surgical planning and robotic-assisted minimally invasive sur...
BACKGROUND: A trainer for online laparoscopic surgical skills assessment based on the performance of experts and nonexperts is presented. The system u...
OBJECTIVES: To evaluate the feasibility of robot-assisted single-port (SP) transvesical partial prostatectomy (TVPP) using a novel purpose-built SP su...
Reduced grip strength, resulting in difficulties in performing daily activities, is a common problem in the population of older adults. Newly develope...
There is substantial interest in assessing how exposure to environmental mixtures, such as chemical mixtures, affect child health. Researchers are als...
BACKGROUND: In the last few years, there has been an increasing interest in the use of robotic devices to objectively quantify motor performance of pa...