AIMC Topic: Multimodal Imaging

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Supervised learning based multimodal MRI brain tumour segmentation using texture features from supervoxels.

Computer methods and programs in biomedicine
BACKGROUND: Accurate segmentation of brain tumour in magnetic resonance images (MRI) is a difficult task due to various tumour types. Using information and features from multimodal MRI including structural MRI and isotropic (p) and anisotropic (q) co...

Use of multimodality imaging and artificial intelligence for diagnosis and prognosis of early stages of Alzheimer's disease.

Translational research : the journal of laboratory and clinical medicine
Alzheimer's disease (AD) is a major neurodegenerative disease and the most common cause of dementia. Currently, no treatment exists to slow down or stop the progression of AD. There is converging belief that disease-modifying treatments should focus ...

Quantitative surface analysis of combined MRI and PET enhances detection of focal cortical dysplasias.

NeuroImage
OBJECTIVE: Focal cortical dysplasias (FCDs) often cause pharmacoresistant epilepsy, and surgical resection can lead to seizure-freedom. Magnetic resonance imaging (MRI) and positron emission tomography (PET) play complementary roles in FCD identifica...

Zero-Echo-Time and Dixon Deep Pseudo-CT (ZeDD CT): Direct Generation of Pseudo-CT Images for Pelvic PET/MRI Attenuation Correction Using Deep Convolutional Neural Networks with Multiparametric MRI.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Accurate quantification of uptake on PET images depends on accurate attenuation correction in reconstruction. Current MR-based attenuation correction methods for body PET use a fat and water map derived from a 2-echo Dixon MRI sequence in which bone ...

Multimodal Imaging in Diabetic Macular Edema.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Throughout ophthalmic history it has been shown that progress has gone hand in hand with technological breakthroughs. In the past, fluorescein angiography and fundus photographs were the most commonly used imaging modalities in the management of diab...

An advanced MRI and MRSI data fusion scheme for enhancing unsupervised brain tumor differentiation.

Computers in biology and medicine
Proton Magnetic Resonance Spectroscopic Imaging (H MRSI) has shown great potential in tumor diagnosis since it provides localized biochemical information discriminating different tissue types, though it typically has low spatial resolution. Magnetic ...

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...

3D Deep Learning for Multi-modal Imaging-Guided Survival Time Prediction of Brain Tumor Patients.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
High-grade glioma is the most aggressive and severe brain tumor that leads to death of almost 50% patients in 1-2 years. Thus, accurate prognosis for glioma patients would provide essential guidelines for their treatment planning. Conventional surviv...

Diagnosis of Alzheimer's Disease Using View-Aligned Hypergraph Learning with Incomplete Multi-modality Data.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Effectively utilizing incomplete multi-modality data for diagnosis of Alzheimer's disease (AD) is still an area of active research. Several multi-view learning methods have recently been developed to deal with missing data, with each view correspondi...

Multimodal US-gamma imaging using collaborative robotics for cancer staging biopsies.

International journal of computer assisted radiology and surgery
PURPOSE: The staging of female breast cancer requires detailed information about the level of cancer spread through the lymphatic system. Common practice to obtain this information for patients with early-stage cancer is sentinel lymph node (SLN) bio...