Jiaofen Nan
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View article: An Automatic Brain Cortex Segmentation Technique Based on Dynamic Recalibration and Region Awareness
An Automatic Brain Cortex Segmentation Technique Based on Dynamic Recalibration and Region Awareness Open
To address the limitations in the accuracy of current cerebral cortex structure segmentation methods, this study proposes an automatic segmentation network based on dynamic recalibration and region awareness. The network is an improved ver…
View article: UPMAD-Net: A Brain Tumor Segmentation Network with Uncertainty Guidance and Adaptive Multimodal Feature Fusion
UPMAD-Net: A Brain Tumor Segmentation Network with Uncertainty Guidance and Adaptive Multimodal Feature Fusion Open
Background: Brain tumor segmentation has a significant impact on the diagnosis and treatment of brain tumors. Accurate brain tumor segmentation remains challenging due to their irregular shapes, vague boundaries, and high variability. Obje…
View article: Myocardial Region-guided Feature Aggregation Net for Automatic Coronary artery Segmentation and Stenosis Assessment using Coronary Computed Tomography Angiography
Myocardial Region-guided Feature Aggregation Net for Automatic Coronary artery Segmentation and Stenosis Assessment using Coronary Computed Tomography Angiography Open
Coronary artery disease (CAD) remains a leading cause of mortality worldwide, requiring accurate segmentation and stenosis detection using Coronary Computed Tomography angiography (CCTA). Existing methods struggle with challenges such as l…
View article: 3D lymphoma segmentation on PET/CT images via multi‐scale information fusion with cross‐attention
3D lymphoma segmentation on PET/CT images via multi‐scale information fusion with cross‐attention Open
Background Accurate segmentation of diffuse large B‐cell lymphoma (DLBCL) lesions is challenging due to their complex patterns in medical imaging. Traditional methods often struggle to delineate these lesions accurately. Objective This stu…
View article: Application of Porous Materials in Photocatalytic Treatment of Wastewater
Application of Porous Materials in Photocatalytic Treatment of Wastewater Open
With the increasing environmental water pollution, there is an increasing demand for efficient and sustainable wastewater treatment technologies. Photocatalysis, as an environmentally friendly oxidation technology, shows significant promis…
View article: MsMorph: An Unsupervised pyramid learning network for brain image registration
MsMorph: An Unsupervised pyramid learning network for brain image registration Open
In the field of medical image analysis, image registration is a crucial technique. Despite the numerous registration models that have been proposed, existing methods still fall short in terms of accuracy and interpretability. In this paper…
View article: Stepwise Discriminant Analysis based Optimal Frequency Band Selection and Ensemble Learning for Same Limb MI Recognition
Stepwise Discriminant Analysis based Optimal Frequency Band Selection and Ensemble Learning for Same Limb MI Recognition Open
Same limb motor imagery (MI) brain-computer interfaces can effectively overcome the cognitive disassociation problem of the traditional different-limb MI paradigm, and they can reduce the patient burden and extend the functionality of exte…
View article: VMD based wavelet hybrid denoising and improved FBCCA algorithm: A new technique for wearable SSVEP recognit ion
VMD based wavelet hybrid denoising and improved FBCCA algorithm: A new technique for wearable SSVEP recognit ion Open
The brain-computer interface (BCI) based on steady-state visual evoked potential (SSVEP) has gained increasing attention due to its non-invasiveness, low user training requirement, and high information transfer rate. In order to enhance th…
View article: Density-Based Discriminative Nonnegative Representation Model for Imbalanced Classification
Density-Based Discriminative Nonnegative Representation Model for Imbalanced Classification Open
Representation-based methods have found widespread applications in various classification tasks. However, these methods cannot deal effectively with imbalanced data scenarios. They tend to neglect the importance of minority samples, result…
View article: White Matter Fiber Tracking Method with Adaptive Correction of Tracking Direction
White Matter Fiber Tracking Method with Adaptive Correction of Tracking Direction Open
Background. The deterministic fiber tracking method has the advantage of high computational efficiency and good repeatability, making it suitable for the noninvasive estimation of brain structural connectivity in clinical fields. To addres…
View article: 3D Lymphoma Segmentation on PET/CT Images via Multi-Scale Information Fusion with Cross-Attention
3D Lymphoma Segmentation on PET/CT Images via Multi-Scale Information Fusion with Cross-Attention Open
Background: Accurate segmentation of diffuse large B-cell lymphoma (DLBCL) lesions is challenging due to their complex patterns in medical imaging. Objective: This study aims to develop a precise segmentation method for DLBCL using 18F-Flu…
View article: Fiber Tracking Method with Adaptive Selection of Peak Direction Based on CSD Model
Fiber Tracking Method with Adaptive Selection of Peak Direction Based on CSD Model Open
As a multi-fiber tracking model, the constrained spherical deconvolution (CSD) model is widely used in the field of fiber reconstruction. The CSD model has shown good reconstruction capabilities for crossing fibers in low anisotropy region…
View article: Functional division of the dorsal striatum based on a graph neural network
Functional division of the dorsal striatum based on a graph neural network Open
The dorsal striatum, an essential nucleus in subcortical areas, has a crucial role in controlling a variety of complex cognitive behaviors; however, few studies have been conducted in recent years to explore the functional subregions of t…
View article: An Improved VMD and Wavelet Hybrid Denoising Model for Wearable SSVEP-BCI
An Improved VMD and Wavelet Hybrid Denoising Model for Wearable SSVEP-BCI Open
The brain-computer interface (BCI) based on steady-state visual evoked potentials (SSVEP) has attracted considerable attention due to its non-invasiveness, low user training requirements, and efficient information transfer rate. To optimiz…
View article: A Stepwise Discriminant Analysis and FBCSP Feature Selection Strategy for EEG MI Recognition
A Stepwise Discriminant Analysis and FBCSP Feature Selection Strategy for EEG MI Recognition Open
Accurate decoding of brain intentions is a pivotal technology within Brain-Computer Interface (BCI) systems that rely on Motor Imagery (MI). The effective extraction of information features plays a critical role in the precise decoding of …
View article: A Robust Deep Learning Method with Uncertainty Estimation for the Pathological Classification of Renal Cell Carcinoma based on CT Images
A Robust Deep Learning Method with Uncertainty Estimation for the Pathological Classification of Renal Cell Carcinoma based on CT Images Open
Objectives To develop and validate a deep learning-based diagnostic model incorporating uncertainty estimation so as to facilitate radiologists in the preoperative differentiation of the pathological subtypes of renal cell carcinoma (RCC) …
View article: Deep learning-based diagnosis of disease activity in patients with Graves’ orbitopathy using orbital SPECT/CT
Deep learning-based diagnosis of disease activity in patients with Graves’ orbitopathy using orbital SPECT/CT Open
Purpose Orbital [ 99m Tc]TcDTPA orbital single-photon emission computed tomography (SPECT)/CT is an important method for assessing inflammatory activity in patients with Graves’ orbitopathy (GO). However, interpreting the results requires …
View article: MLA-BIN: Model-level Attention and Batch-instance Style Normalization for Domain Generalization of Federated Learning on Medical Image Segmentation
MLA-BIN: Model-level Attention and Batch-instance Style Normalization for Domain Generalization of Federated Learning on Medical Image Segmentation Open
The privacy protection mechanism of federated learning (FL) offers an effective solution for cross-center medical collaboration and data sharing. In multi-site medical image segmentation, each medical site serves as a client of FL, and its…
View article: Methodological Research on Image Registration Based on Human Brain Tissue In Vivo
Methodological Research on Image Registration Based on Human Brain Tissue In Vivo Open
As one of the critical steps in brain imaging analysis and processing, brain image registration plays a significant role. In this paper, we proposed a technique of human brain image registration based on tissue morphology in vivo to addres…
View article: An Adaptive Channel Selection and Graph ResNet Based Algorithm for Motor Imagery Classification
An Adaptive Channel Selection and Graph ResNet Based Algorithm for Motor Imagery Classification Open
In Brain-Computer interface (BCI) applications, achieving accurate control relies heavily on the classification accuracy and efficiency of motor imagery electroencephalogram (EEG) signals. However, factors such as mutual interference betwe…
View article: Deep Learning-Based Diagnosis of Disease Activity in Patients with Graves’ Orbitopathy Using Orbital SPECT/CT
Deep Learning-Based Diagnosis of Disease Activity in Patients with Graves’ Orbitopathy Using Orbital SPECT/CT Open
Purpose Orbital 99mTc-DTPA SPECT/CT is an important new method for the assessment of inflammatory activity in patients with Graves' Orbitopathy (GO), but it consumes a heavy workload for physicians for interpretation. We aim to propose an …
View article: Functional differentiation of the dorsal striatum: a coordinate-based neuroimaging meta-analysis
Functional differentiation of the dorsal striatum: a coordinate-based neuroimaging meta-analysis Open
Different subregions of the caudate and putamen assume different roles in processing complex cognitive behaviors. Functional division of the dorsal striatum identified specific roles of 15 different subregions, reflecting differences and c…
View article: A new method incorporating deep learning with shape priors for left ventricular segmentation in myocardial perfusion SPECT images
A new method incorporating deep learning with shape priors for left ventricular segmentation in myocardial perfusion SPECT images Open
Background: The assessment of left ventricular (LV) function by myocardial perfusion SPECT (MPS) relies on accurate myocardial segmentation. The purpose of this paper is to develop and validate a new method incorporating deep learning with…
View article: A New Method on Construction of Brain Effective Connectivity Based on Functional Magnetic Resonance Imaging
A New Method on Construction of Brain Effective Connectivity Based on Functional Magnetic Resonance Imaging Open
Most of the existing methods about the causal relationship based on functional magnetic resonance imaging (fMRI) data are either the hypothesis-driven methods or based on a linear model, which can result in the deviation for detecting the …
View article: Detection of Premature Ventricular Contractions using 12-lead Dynamic ECG based on Squeeze-Excitation Residual Network
Detection of Premature Ventricular Contractions using 12-lead Dynamic ECG based on Squeeze-Excitation Residual Network Open
Premature ventricular contraction (PVC) is a very common arrhythmia that can originate in any part of the ventricle and is one of the important causes of sudden cardiac death. Timely and rapid detection of PVC on dynamic electrocardiogram …
View article: A Medical Image Registration Method Based on Progressive Images
A Medical Image Registration Method Based on Progressive Images Open
Background. Medical image registration is an essential task for medical image analysis in various applications. In this work, we develop a coarse-to-fine medical image registration method based on progressive images and SURF algorithm (PI-…
View article: Coil combination using linear deconvolution in k-space for phase imaging
Coil combination using linear deconvolution in k-space for phase imaging Open
The proposed method provides an effective and efficient approach to combine multiple coil image in parallel MRI reconstruction, and has potential to benefit routine clinical practice in the future.
View article: White Matter Microstructural Similarity and Diversity of Functional Constipation and Constipation-predominant Irritable Bowel Syndrome
White Matter Microstructural Similarity and Diversity of Functional Constipation and Constipation-predominant Irritable Bowel Syndrome Open
These results may improve our understanding of the pathophysiological mechanisms underlying different types of constipation.