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Generalization of deep learning models for ultra-low-count amyloid PET/MRI using transfer learning.

European journal of nuclear medicine and molecular imaging
PURPOSE: We aimed to evaluate the performance of deep learning-based generalization of ultra-low-count amyloid PET/MRI enhancement when applied to studies acquired with different scanning hardware and protocols.

Can robotic gait rehabilitation plus Virtual Reality affect cognitive and behavioural outcomes in patients with chronic stroke? A randomized controlled trial involving three different protocols.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: The rehabilitation of cognitive and behavioral abnormalities in individuals with stroke is essential for promoting patient's recovery and autonomy. The aim of our study is to evaluate the effects of robotic neurorehabilitation using Lokom...

Deep-Learning F-FDG Uptake Classification Enables Total Metabolic Tumor Volume Estimation in Diffuse Large B-Cell Lymphoma.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Total metabolic tumor volume (TMTV), calculated from F-FDG PET/CT baseline studies, is a prognostic factor in diffuse large B-cell lymphoma (DLBCL) whose measurement requires the segmentation of all malignant foci throughout the body. No consensus cu...

Self-co-attention neural network for anatomy segmentation in whole breast ultrasound.

Medical image analysis
The automated whole breast ultrasound (AWBUS) is a new breast imaging technique that can depict the whole breast anatomy. To facilitate the reading of AWBUS images and support the breast density estimation, an automatic breast anatomy segmentation me...

BIRADS features-oriented semi-supervised deep learning for breast ultrasound computer-aided diagnosis.

Physics in medicine and biology
We propose a novel BIRADS-SSDL network that integrates clinically-approved breast lesion characteristics (BIRADS features) into task-oriented semi-supervised deep learning (SSDL) for accurate diagnosis of ultrasound (US) images with a small training ...

A Novel Robotic Endoscopic Device Used for Operative Hysteroscopy.

Journal of minimally invasive gynecology
To trial the use of a novel endoscopic robot that functions using concentric tube robots, enabling 2-handed surgery in small spaces, in a bioengineering laboratory. This was a feasibility study of the endoscopic robot for hysteroscopic applications, ...

Comparing the Bone Healing After Cold Ablation Robot-Guided Er:YAG Laser Osteotomy and Piezoelectric Osteotomy-A Pilot Study in a Minipig Mandible.

Lasers in surgery and medicine
BACKGROUND AND OBJECTIVE: To take major advantage of erbium-doped yttrium aluminium garnet (Er:YAG) lasers in osteotomy-like freedom of cutting geometries and high accuracy-the integration and miniaturization of the robot, laser, and navigation techn...

Differentiating molecular etiologies of Angelman syndrome through facial phenotyping using deep learning.

American journal of medical genetics. Part A
Angelman syndrome (AS) is caused by several genetic mechanisms that impair the expression of maternally-inherited UBE3A through deletions, paternal uniparental disomy (UPD), UBE3A pathogenic variants, or imprinting defects. Current methods of differe...

Diagnostic evaluation of a deep learning model for optical diagnosis of colorectal cancer.

Nature communications
Colonoscopy is commonly used to screen for colorectal cancer (CRC). We develop a deep learning model called CRCNet for optical diagnosis of CRC by training on 464,105 images from 12,179 patients and test its performance on 2263 patients from three in...