238 citations · 1.1k across the 35 of their papers we have counts for
35 papers
Hyper-Fusion Network for Semi-Automatic Segmentation of Skin Lesions
Lei Bi, Michael Fulham, Jinman Kim
Automatic skin lesion segmentation methods based on fully convolutional networks (FCNs) are regarded as the state-of-the-art for accuracy. When there are, however, insufficient tra…
A Review of Predictive and Contrastive Self-supervised Learning for Medical Images
Wei-Chien Wang, Euijoon Ahn, Dagan Feng +1
Over the last decade, supervised deep learning on manually annotated big data has been progressing significantly on computer vision tasks. But the application of deep learning in m…
Z-SSMNet: Zonal-aware Self-supervised Mesh Network for Prostate Cancer Detection and Diagnosis with Bi-parametric MRI
Yuan Yuan, Euijoon Ahn, Dagan Feng +2
Bi-parametric magnetic resonance imaging (bpMRI) has become a pivotal modality in the detection and diagnosis of clinically significant prostate cancer (csPCa). Developing AI-based…
Brain Tumor Sequence Registration with Non-iterative Coarse-to-fine Networks and Dual Deep Supervision
Mingyuan Meng, Lei Bi, Dagan Feng +1
In this study, we focus on brain tumor sequence registration between pre-operative and follow-up Magnetic Resonance Imaging (MRI) scans of brain glioma patients, in the context of…
Radiomics-enhanced Deep Multi-task Learning for Outcome Prediction in Head and Neck Cancer
Mingyuan Meng, Lei Bi, Dagan Feng +1
Outcome prediction is crucial for head and neck cancer patients as it can provide prognostic information for early treatment planning. Radiomics methods have been widely used for o…
Unsupervised Landmark Detection Based Spatiotemporal Motion Estimation for 4D Dynamic Medical Images
Yuyu Guo, Lei Bi, Dongming Wei +6
Motion estimation is a fundamental step in dynamic medical image processing for the assessment of target organ anatomy and function. However, existing image-based motion estimation…
DeepMTS: Deep Multi-task Learning for Survival Prediction in Patients with Advanced Nasopharyngeal Carcinoma using Pretreatment PET/CT
Mingyuan Meng, Bingxin Gu, Lei Bi +3
Nasopharyngeal Carcinoma (NPC) is a malignant epithelial cancer arising from the nasopharynx. Survival prediction is a major concern for NPC patients, as it provides early prognost…
A Spatial Guided Self-supervised Clustering Network for Medical Image Segmentation
Euijoon Ahn, Dagan Feng, Jinman Kim
The segmentation of medical images is a fundamental step in automated clinical decision support systems. Existing medical image segmentation methods based on supervised deep learni…
Benchmarking for Biomedical Natural Language Processing Tasks with a Domain Specific ALBERT
Usman Naseem, Adam G. Dunn, Matloob Khushi +1
The availability of biomedical text data and advances in natural language processing (NLP) have made new applications in biomedical NLP possible. Language models trained or fine tu…
Self-supervised Representation Learning Framework for Remote Physiological Measurement Using Spatiotemporal Augmentation Loss
Hao Wang, Euijoon Ahn, Jinman Kim
Recent advances in supervised deep learning methods are enabling remote measurements of photoplethysmography-based physiological signals using facial videos. The performance of the…
Classifying vaccine sentiment tweets by modelling domain-specific representation and commonsense knowledge into context-aware attentive GRU
Usman Naseem, Matloob Khushi, Jinman Kim +1
Vaccines are an important public health measure, but vaccine hesitancy and refusal can create clusters of low vaccine coverage and reduce the effectiveness of vaccination programs.…
Spatio-Temporal Dual-Stream Neural Network for Sequential Whole-Body PET Segmentation
Kai-Chieh Liang, Lei Bi, Ashnil Kumar +2
Sequential whole-body 18F-Fluorodeoxyglucose (FDG) positron emission tomography (PET) scans are regarded as the imaging modality of choice for the assessment of treatment response…
Predicting Distant Metastases in Soft-Tissue Sarcomas from PET-CT scans using Constrained Hierarchical Multi-Modality Feature Learning
Yige Peng, Lei Bi, Ashnil Kumar +3
Distant metastases (DM) refer to the dissemination of tumors, usually, beyond the organ where the tumor originated. They are the leading cause of death in patients with soft-tissue…
Graph-Based Intercategory and Intermodality Network for Multilabel Classification and Melanoma Diagnosis of Skin Lesions in Dermoscopy and Clinical Images
Xiaohang Fu, Lei Bi, Ashnil Kumar +2
The identification of melanoma involves an integrated analysis of skin lesion images acquired using the clinical and dermoscopy modalities. Dermoscopic images provide a detailed vi…
Prediction of 5-year Progression-Free Survival in Advanced Nasopharyngeal Carcinoma with Pretreatment PET/CT using Multi-Modality Deep Learning-based Radiomics
Bingxin Gu, Mingyuan Meng, Lei Bi +3
Objective: Deep Learning-based Radiomics (DLR) has achieved great success in medical image analysis and has been considered a replacement for conventional radiomics that relies on…
Enhancing Medical Image Registration via Appearance Adjustment Networks
Mingyuan Meng, Lei Bi, Michael Fulham +2
Deformable image registration is fundamental for many medical image analyses. A key obstacle for accurate image registration lies in image appearance variations such as the variati…
Attention-Enhanced Cross-Task Network for Analysing Multiple Attributes of Lung Nodules in CT
Xiaohang Fu, Lei Bi, Ashnil Kumar +2
Accurate characterisation of visual attributes such as spiculation, lobulation, and calcification of lung nodules is critical in cancer management. The characterisation of these at…
BioALBERT: A Simple and Effective Pre-trained Language Model for Biomedical Named Entity Recognition
Usman Naseem, Matloob Khushi, Vinay Reddy +3
In recent years, with the growing amount of biomedical documents, coupled with advancement in natural language processing algorithms, the research on biomedical named entity recogn…
Multimodal Spatial Attention Module for Targeting Multimodal PET-CT Lung Tumor Segmentation
Xiaohang Fu, Lei Bi, Ashnil Kumar +2
Multimodal positron emission tomography-computed tomography (PET-CT) is used routinely in the assessment of cancer. PET-CT combines the high sensitivity for tumor detection with PE…
Multi-Modality Information Fusion for Radiomics-based Neural Architecture Search
Yige Peng, Lei Bi, Michael Fulham +2
'Radiomics' is a method that extracts mineable quantitative features from radiographic images. These features can then be used to determine prognosis, for example, predicting the d…
Deep Multi-Scale Resemblance Network for the Sub-class Differentiation of Adrenal Masses on Computed Tomography Images
Lei Bi, Jinman Kim, Tingwei Su +3
The accurate classification of mass lesions in the adrenal glands (adrenal masses), detected with computed tomography (CT), is important for diagnosis and patient management. Adren…
A Spatiotemporal Volumetric Interpolation Network for 4D Dynamic Medical Image
Yuyu Guo, Lei Bi, Euijoon Ahn +3
Dynamic medical imaging is usually limited in application due to the large radiation doses and longer image scanning and reconstruction times. Existing methods attempt to reduce th…
High-parallelism Inception-like Spiking Neural Networks for Unsupervised Feature Learning
Mingyuan Meng, Xingyu Yang, Lei Bi +3
Spiking Neural Networks (SNNs) are brain-inspired, event-driven machine learning algorithms that have been widely recognized in producing ultra-high-energy-efficient hardware. Amon…
Deep Local Global Refinement Network for Stent Analysis in IVOCT Images
Yuyu Guo
Implantation of stents into coronary arteries is a common treatment option for patients with cardiovascular disease. Assessment of safety and efficacy of the stent implantation occ…