AIMC Topic: Multimodal Imaging

Clear Filters Showing 271 to 280 of 311 articles

Differentiation of canine and feline neoplasms using multi-modal imaging and machine learning.

Scientific reports
Canine/feline (sub-)cutaneous tumors, which include lipomas, mastocytomas and soft tissue sarcomas, introduce diagnostic challenges due to inherent tissue heterogeneity, accompanied by diverse clinical pathogenesis. Current study integrates conventio...

Multimodal ultrasound-based radiomics and deep learning for differential diagnosis of O-RADS 4-5 adnexal masses.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Accurate differentiation between benign and malignant adnexal masses is crucial for patients to avoid unnecessary surgical interventions. Ultrasound (US) is the most widely utilized diagnostic and screening tool for gynecological diseases...

AI-powered integration of multimodal imaging in precision medicine for neuropsychiatric disorders.

Cell reports. Medicine
Neuropsychiatric disorders have complex pathological mechanism, pronounced clinical heterogeneity, and a prolonged preclinical phase, which presents a challenge for early diagnosis and development of precise intervention strategies. With the developm...

Does Whole Brain Radiomics on Multimodal Neuroimaging Make Sense in Neuro-Oncology? A Proof of Concept Study.

Studies in health technology and informatics
Employing a whole-brain (WB) mask as a region of interest for extracting radiomic features is a feasible, albeit less common, approach in neuro-oncology research. This study aims to evaluate the relationship between WB radiomic features, derived from...

Deep normative modelling reveals insights into early-stage Alzheimer's disease using multi-modal neuroimaging data.

Alzheimer's research & therapy
BACKGROUND: Exploring the early stages of Alzheimer's disease (AD) is crucial for timely intervention to help manage symptoms and set expectations for affected individuals and their families. However, the study of the early stages of AD involves anal...

[Artificial intelligence-based multimodal fusion diagnosis: advances in precision diagnosis of periodontitis].

Zhonghua kou qiang yi xue za zhi = Zhonghua kouqiang yixue zazhi = Chinese journal of stomatology
Periodontitis is a globally prevalent inflammatory oral disease, affecting approximately 50% of the population worldwide and imposing a substantial burden on patients' health and quality of life. Early and accurate diagnosis is critical for preventin...

Predicting Recurrence in Locally Advanced Rectal Cancer Using Multitask Deep Learning and Multimodal MRI.

Radiology. Imaging cancer
Purpose To develop and validate a deep multitask network, MultiRecNet, for fully automatic prediction of disease-free survival (DFS) in patients with neoadjuvant chemoradiotherapy (nCRT)-treated locally advanced rectal cancer (LARC). Materials and Me...

Innovations in artificial intelligence for pet/mr imaging: Application and performance analysis.

Journal of X-ray science and technology
BackgroundThe primary challenges in PET/MR imaging include prolonged scan durations for both PET and MR components and radiation exposure associated with the PET modality. Artificial intelligence (AI)-based techniques offer a promising approach to ov...

Integrating multimodal imaging and peritumoral features for enhanced prostate cancer diagnosis: A machine learning approach.

PloS one
BACKGROUND: Prostate cancer is a common malignancy in men, and accurately distinguishing between benign and malignant nodules at an early stage is crucial for optimizing treatment. Multimodal imaging (such as ADC and T2) plays an important role in th...