Lichi Zhang
YOU?
Author Swipe
View article: LGAN: An Efficient High-Order Graph Neural Network via the Line Graph Aggregation
LGAN: An Efficient High-Order Graph Neural Network via the Line Graph Aggregation Open
Graph Neural Networks (GNNs) have emerged as a dominant paradigm for graph classification. Specifically, most existing GNNs mainly rely on the message passing strategy between neighbor nodes, where the expressivity is limited by the 1-dime…
View article: Brain Connectivity Network Structure Learning For Brain Disorder Diagnosis
Brain Connectivity Network Structure Learning For Brain Disorder Diagnosis Open
Recent studies in neuroscience highlight the significant potential of brain connectivity networks, which are commonly constructed from functional magnetic resonance imaging (fMRI) data for brain disorder diagnosis. Traditional brain connec…
View article: Structural–Functional Connectivity Coupling in Motor–Brain Networks Following Acute Ischemic Stroke
Structural–Functional Connectivity Coupling in Motor–Brain Networks Following Acute Ischemic Stroke Open
Background: Structural connectivity (SC) and functional connectivity (FC) are pivotal for motor recovery after stroke, yet their interplay (SC-FC coupling) within the motor network during the acute phase of ischemic stroke remains poorly u…
View article: 3D Wavelet Latent Diffusion Model for Whole-Body MR-to-CT Modality Translation
3D Wavelet Latent Diffusion Model for Whole-Body MR-to-CT Modality Translation Open
Magnetic Resonance (MR) imaging plays an essential role in contemporary clinical diagnostics. It is increasingly integrated into advanced therapeutic workflows, such as hybrid Positron Emission Tomography/Magnetic Resonance (PET/MR) imagin…
View article: Segmentation and Classification in Digital Pathology for Glioma Research: Challenges and Deep Learning Approaches
Segmentation and Classification in Digital Pathology for Glioma Research: Challenges and Deep Learning Approaches Open
Biomedical imaging Is an important source of information in cancer research. Characterizations of cancer morphology at onset, progression, and in response to treatment provide complementary information to that gleaned from genomics and cli…
View article: Structure-Guided MR-to-CT Synthesis with Spatial and Semantic Alignments for Attenuation Correction of Whole-Body PET/MR Imaging
Structure-Guided MR-to-CT Synthesis with Spatial and Semantic Alignments for Attenuation Correction of Whole-Body PET/MR Imaging Open
Deep-learning-based MR-to-CT synthesis can estimate the electron density of tissues, thereby facilitating PET attenuation correction in whole-body PET/MR imaging. However, whole-body MR-to-CT synthesis faces several challenges including th…
View article: Prediction of 131I Uptake in Lung Metastases of Differentiated Thyroid Cancer Using Deep Learning
Prediction of 131I Uptake in Lung Metastases of Differentiated Thyroid Cancer Using Deep Learning Open
Objective: An accurate assessment the 131I accumulation capacity in lung metastases of differentiated thyroid cancer (DTC) is pivotal to inform radioiodine therapy and avoid invalid 131I administration. Thus, to devel…
View article: REHRSeg: Unleashing the Power of Self-Supervised Super-Resolution for Resource-Efficient 3D MRI Segmentation
REHRSeg: Unleashing the Power of Self-Supervised Super-Resolution for Resource-Efficient 3D MRI Segmentation Open
High-resolution (HR) 3D magnetic resonance imaging (MRI) can provide detailed anatomical structural information, enabling precise segmentation of regions of interest for various medical image analysis tasks. Due to the high demands of acqu…
View article: Deep embedding convolutional neural network for synthesizing CT image from T1-Weighted MR image
Deep embedding convolutional neural network for synthesizing CT image from T1-Weighted MR image Open
View article: Extraction of dynamic functional connectivity from brain grey matter and white matter for MCI classification
Extraction of dynamic functional connectivity from brain grey matter and white matter for MCI classification Open
Brain functional connectivity (FC) extracted from resting-state fMRI (RS-fMRI) has become a popular approach for diagnosing various neurodegenerative diseases, including Alzheimer's disease (AD) and its prodromal stage, mild cognitive impa…
View article: Functional MRI registration with tissue-specific patch-based functional correlation tensors
Functional MRI registration with tissue-specific patch-based functional correlation tensors Open
Population studies of brain function with resting-state functional magnetic resonance imaging (rs-fMRI) rely on accurate intersubject registration of functional areas. This is typically achieved through registration using high-resolution s…
View article: Exploring diagnosis and imaging biomarkers of Parkinson's disease via iterative canonical correlation analysis based feature selection
Exploring diagnosis and imaging biomarkers of Parkinson's disease via iterative canonical correlation analysis based feature selection Open
View article: Automatic brain labeling via multi-atlas guided fully convolutional networks
Automatic brain labeling via multi-atlas guided fully convolutional networks Open
View article: Learning-based structurally-guided construction of resting-state functional correlation tensors
Learning-based structurally-guided construction of resting-state functional correlation tensors Open
View article: Inter-slice Super-resolution of Magnetic Resonance Images by Pre-training and Self-supervised Fine-tuning
Inter-slice Super-resolution of Magnetic Resonance Images by Pre-training and Self-supervised Fine-tuning Open
In clinical practice, 2D magnetic resonance (MR) sequences are widely adopted. While individual 2D slices can be stacked to form a 3D volume, the relatively large slice spacing can pose challenges for both image visualization and subsequen…
View article: Periaqueductal gray subregions connectivity and its association with micturition desire-awakening function
Periaqueductal gray subregions connectivity and its association with micturition desire-awakening function Open
Purpose Existing literature strongly supports the idea that children with primary nocturnal enuresis (PNE) have a delayed brainstem maturation. However, the connection between pre-micturition arousal responses and brain functional connecti…
View article: Two-stage Cytopathological Image Synthesis for Augmenting Cervical Abnormality Screening
Two-stage Cytopathological Image Synthesis for Augmenting Cervical Abnormality Screening Open
Automatic thin-prep cytologic test (TCT) screening can assist pathologists in finding cervical abnormality towards accurate and efficient cervical cancer diagnosis. Current automatic TCT screening systems mostly involve abnormal cervical c…
View article: CSSNet: Cascaded spatial shift network for multi-organ segmentation
CSSNet: Cascaded spatial shift network for multi-organ segmentation Open
Multi-organ segmentation is vital for clinical diagnosis and treatment. Although CNN and its extensions are popular in organ segmentation, they suffer from the local receptive field. In contrast, MultiLayer-Perceptron-based models (e.g., M…
View article: A Radiographic Analysis of Coronal Morphological Parameters of Lower Limbs in Chinese Non‐knee Osteoarthritis Populations
A Radiographic Analysis of Coronal Morphological Parameters of Lower Limbs in Chinese Non‐knee Osteoarthritis Populations Open
Objectives Analyzing the lower limb coronal morphological parameters in populations without knee osteoarthritis (KOA) holds significant value in predicting, diagnosing, and formulating surgical strategies for KOA. This study aimed to compr…
View article: Uni-COAL: A Unified Framework for Cross-Modality Synthesis and Super-Resolution of MR Images
Uni-COAL: A Unified Framework for Cross-Modality Synthesis and Super-Resolution of MR Images Open
Cross-modality synthesis (CMS), super-resolution (SR), and their combination (CMSR) have been extensively studied for magnetic resonance imaging (MRI). Their primary goals are to enhance the imaging quality by synthesizing the desired moda…
View article: Progressive Attention Guidance for Whole Slide Vulvovaginal Candidiasis Screening
Progressive Attention Guidance for Whole Slide Vulvovaginal Candidiasis Screening Open
Vulvovaginal candidiasis (VVC) is the most prevalent human candidal infection, estimated to afflict approximately 75% of all women at least once in their lifetime. It will lead to several symptoms including pruritus, vaginal soreness, and …
View article: AdLER: Adversarial Training with Label Error Rectification for One-Shot Medical Image Segmentation
AdLER: Adversarial Training with Label Error Rectification for One-Shot Medical Image Segmentation Open
Accurate automatic segmentation of medical images typically requires large datasets with high-quality annotations, making it less applicable in clinical settings due to limited training data. One-shot segmentation based on learned transfor…
View article: CellGAN: Conditional Cervical Cell Synthesis for Augmenting Cytopathological Image Classification
CellGAN: Conditional Cervical Cell Synthesis for Augmenting Cytopathological Image Classification Open
Automatic examination of thin-prep cytologic test (TCT) slides can assist pathologists in finding cervical abnormality for accurate and efficient cancer screening. Current solutions mostly need to localize suspicious cells and classify abn…
View article: CT-based Subchondral Bone Microstructural Analysis in Knee Osteoarthritis via MR-Guided Distillation Learning
CT-based Subchondral Bone Microstructural Analysis in Knee Osteoarthritis via MR-Guided Distillation Learning Open
Background: MR-based subchondral bone effectively predicts knee osteoarthritis. However, its clinical application is limited by the cost and time of MR. Purpose: We aim to develop a novel distillation-learning-based method named SRRD for s…
View article: Automatic risk prediction of intracranial aneurysm on CTA image with convolutional neural networks and radiomics analysis
Automatic risk prediction of intracranial aneurysm on CTA image with convolutional neural networks and radiomics analysis Open
Background Intracranial aneurysm (IA) is a nodular protrusion of the arterial wall caused by the localized abnormal enlargement of the lumen of a brain artery, which is the primary cause of subarachnoid hemorrhage. Accurate rupture risk pr…
View article: Learning Better Contrastive View from Radiologist's Gaze
Learning Better Contrastive View from Radiologist's Gaze Open
Recent self-supervised contrastive learning methods greatly benefit from the Siamese structure that aims to minimizing distances between positive pairs. These methods usually apply random data augmentation to input images, expecting the au…
View article: Cartilage morphometry and magnetic susceptibility measurement for knee osteoarthritis with automatic cartilage segmentation
Cartilage morphometry and magnetic susceptibility measurement for knee osteoarthritis with automatic cartilage segmentation Open
The 3D_WATS cartilage MR imaging allows simultaneously automated assessment of cartilage morphometry and magnetic susceptibility for evaluating the severity of OA using the proposed cartilage segmentation method.
View article: Domain Generalization for Mammographic Image Analysis with Contrastive Learning
Domain Generalization for Mammographic Image Analysis with Contrastive Learning Open
The deep learning technique has been shown to be effectively addressed several image analysis tasks in the computer-aided diagnosis scheme for mammography. The training of an efficacious deep learning model requires large data with diverse…
View article: Arbitrary Reduction of MRI Inter-slice Spacing Using Hierarchical Feature Conditional Diffusion
Arbitrary Reduction of MRI Inter-slice Spacing Using Hierarchical Feature Conditional Diffusion Open
Magnetic resonance (MR) images collected in 2D scanning protocols typically have large inter-slice spacing, resulting in high in-plane resolution but reduced through-plane resolution. Super-resolution techniques can reduce the inter-slice …
View article: Enhanced brain parcellation via abnormality inpainting for neuroimage-based consciousness evaluation of hydrocephalus patients by lumbar drainage
Enhanced brain parcellation via abnormality inpainting for neuroimage-based consciousness evaluation of hydrocephalus patients by lumbar drainage Open