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Magnetic Resonance Imaging

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Complex-valued neural networks to speed-up MR thermometry during hyperthermia using Fourier PD and PDUNet.

Scientific reports
Hyperthermia (HT) in combination with radio- and/or chemotherapy has become an accepted cancer treatment for distinct solid tumour entities. In HT, tumour tissue is exogenously heated to temperatures between 39 and 43 °C for 60 min. Temperature monit...

Unsupervised brain MRI tumour segmentation via two-stage image synthesis.

Medical image analysis
Deep learning shows promise in automated brain tumour segmentation, but it depends on costly expert annotations. Recent advances in unsupervised learning offer an alternative by using synthetic data for training. However, the discrepancy between real...

Deep-learning synthetized 4DCT from 4DMRI of the abdominal site in carbon-ion radiotherapy.

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: To investigate the feasibility of deep-learning-based synthetic 4DCT (4D-sCT) generation from 4DMRI data of abdominal patients undergoing Carbon Ion Radiotherapy (CIRT).

A fine-tuned convolutional neural network model for accurate Alzheimer's disease classification.

Scientific reports
Alzheimer's disease (AD) is one of the primary causes of dementia in the older population, affecting memories, cognitive levels, and the ability to accomplish simple activities gradually. Timely intervention and efficient control of the disease prove...

A semantic segmentation model for automatic precise identification of pituitary microadenomas with preoperative MRI.

Neuroradiology
PURPOSE: Magnetic resonance imaging (MRI) is an essential technique for diagnosing pituitary adenomas; however, it is also challenging for neurosurgeons to use it to precisely identify some types of microadenomas. A novel neural network model was dev...

SFM-Net: Semantic Feature-Based Multi-Stage Network for Unsupervised Image Registration.

IEEE journal of biomedical and health informatics
It is difficult for general registration methods to establish the fine correspondence between images with complex anatomical structures. To overcome the above problem, this work presents SFM-Net, an unsupervised multi-stage semantic feature-based net...

CorrMorph: Unsupervised Deformable Brain MRI Registration Based on Correlation Mining.

IEEE journal of biomedical and health informatics
Deformable image registration, as a fundamental prerequisite for many medical image analysis tasks, has received considerable attention. However, existing methods suffer from two key issues: 1) single-stream methods that stack moving and fixed images...

LGG-NeXt: A Next Generation CNN and Transformer Hybrid Model for the Diagnosis of Alzheimer's Disease Using 2D Structural MRI.

IEEE journal of biomedical and health informatics
Incurable Alzheimer's disease (AD) plagues many elderly people and families. It is important to accurately diagnose and predict it at an early stage. However, the existing methods have shortcomings, such as inability to learn local and global informa...

Self-Supervised Multi-Scale Multi-Modal Graph Pool Transformer for Sellar Region Tumor Diagnosis.

IEEE journal of biomedical and health informatics
The sellar region tumor is a brain tumor that only exists in the brain sellar, which affects the central nervous system. The early diagnosis of the sellar region tumor subtypes helps clinicians better understand the best treatment and recovery of pat...