AIMC Topic: Magnetic Resonance Imaging

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A Natural Language Processing-based Model to Automate MRI Brain Protocol Selection and Prioritization.

Academic radiology
RATIONALE AND OBJECTIVES: Incorrect imaging protocol selection can contribute to increased healthcare cost and waste. To help healthcare providers improve the quality and safety of medical imaging services, we developed and evaluated three natural la...

Detection of Mild Traumatic Brain Injury by Machine Learning Classification Using Resting State Functional Network Connectivity and Fractional Anisotropy.

Journal of neurotrauma
Traumatic brain injury (TBI) may adversely affect a person's thinking, memory, personality, and behavior. While mild TBI (mTBI) diagnosis is challenging, there is a risk for long-term psychiatric, neurologic, and psychosocial problems in some patient...

Artificial Neural Networks approach to pharmacokinetic model selection in DCE-MRI studies.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: In pharmacokinetic analysis of Dynamic Contrast Enhanced MRI data, a descriptive physiological model should be selected properly out of a set of candidate models. Classical techniques suggested for this purpose suffer from issues like comput...

First report of robot-assisted transperineal fusion versus off-target biopsy in patients undergoing repeat prostate biopsy.

World journal of urology
PURPOSE: To clarify the value of targeted versus off-target biopsies in men with a suspicion of prostate cancer (PC) and a visible lesion in multi-parametric magnetic resonance imaging (mpMRI) using transperineal robot-assisted biopsy.

EEG and fMRI agree: Mental arithmetic is the easiest form of imagery to detect.

Consciousness and cognition
fMRI and EEG during mental imagery provide alternative methods of detecting awareness in patients with disorders of consciousness (DOC) without reliance on behaviour. Because using fMRI in patients with DOC is difficult, studies increasingly employ E...

DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks.

IEEE transactions on medical imaging
In this paper, we propose DeepCut, a method to obtain pixelwise object segmentations given an image dataset labelled weak annotations, in our case bounding boxes. It extends the approach of the well-known GrabCut [1] method to include machine learnin...

An ultrasound image navigation robotic prostate brachytherapy system based on US to MRI deformable image registration method.

Hellenic journal of nuclear medicine
OBJECTIVE: This paper describes an ultrasound image navigation robotic prostate brachytherapy system. It uses a 2D ultrasound (US) probe rigidly fixed to a robotic needle insertion mechanism. Combined with the US probe registration and image registra...

Preoperative assessment of lymph node metastasis in endometrial cancer: A Korean Gynecologic Oncology Group study.

Cancer
BACKGROUND: Previously proposed criteria for preoperatively identifying endometrial cancer patients at low risk for lymph node metastasis remain to be verified. For this purpose, a prospective, multicenter observational study was performed.

Unsupervised boundary delineation of spinal neural foramina using a multi-feature and adaptive spectral segmentation.

Medical image analysis
As a common disease in the elderly, neural foramina stenosis (NFS) brings a significantly negative impact on the quality of life due to its symptoms including pain, disability, fall risk and depression. Accurate boundary delineation is essential to t...

Diffuse intrinsic pontine gliomas in children: Interest of robotic frameless assisted biopsy. A technical note.

Neuro-Chirurgie
INTRODUCTION: Diffuse intrinsic pontine gliomas (DIPG) constitute 10-15% of all brain tumors in the pediatric population; currently prognosis remains poor, with an overall survival of 7-14 months. Recently the indication of DIPG biopsy has been enlar...