Dakai Jin
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View article: Vision-Language Models for Automated 3D PET/CT Report Generation
Vision-Language Models for Automated 3D PET/CT Report Generation Open
Positron emission tomography/computed tomography (PET/CT) is essential in oncology, yet the rapid expansion of scanners has outpaced the availability of trained specialists, making automated PET/CT report generation (PETRG) increasingly im…
View article: Thyroid nodule and lymph node metastasis assessment from ultrasound images using deep learning
Thyroid nodule and lymph node metastasis assessment from ultrasound images using deep learning Open
Objectives The preoperative differentiation of thyroid nodules into benign thyroid nodules (BTN), non-metastatic malignant thyroid nodules (NMTN), and metastatic malignant thyroid nodules (MMTN) is critical for guiding clinical management …
View article: Exploiting Semantic Asymmetry to Enhance the Accuracy of Gross Tumor Volume Delineation in Nasopharyngeal Carcinoma on Planning CT
Exploiting Semantic Asymmetry to Enhance the Accuracy of Gross Tumor Volume Delineation in Nasopharyngeal Carcinoma on Planning CT Open
View article: 521 | HAIPI: AN AI‐BASED MODEL IMPROVING THE INTERNATIONAL PROGNOSTIC INDEX FOR DLBCL
521 | HAIPI: AN AI‐BASED MODEL IMPROVING THE INTERNATIONAL PROGNOSTIC INDEX FOR DLBCL Open
View article: Towards a Comprehensive, Efficient and Promptable Anatomic Structure Segmentation Model Using 3D Whole-Body CT Scans
Towards a Comprehensive, Efficient and Promptable Anatomic Structure Segmentation Model Using 3D Whole-Body CT Scans Open
Segment anything model (SAM) demonstrates strong generalization ability on natural image segmentation. However, its direct adaptation in medical image segmentation tasks shows significant performance drops. It also requires an excessive nu…
View article: From Slices to Sequences: Autoregressive Tracking Transformer for Cohesive and Consistent 3D Lymph Node Detection in CT Scans
From Slices to Sequences: Autoregressive Tracking Transformer for Cohesive and Consistent 3D Lymph Node Detection in CT Scans Open
Lymph node (LN) assessment is an essential task in the routine radiology workflow, providing valuable insights for cancer staging, treatment planning and beyond. Identifying scatteredly-distributed and low-contrast LNs in 3D CT scans is hi…
View article: From Histopathology Images to Cell Clouds: Learning Slide Representations with Hierarchical Cell Transformer
From Histopathology Images to Cell Clouds: Learning Slide Representations with Hierarchical Cell Transformer Open
It is clinically crucial and potentially very beneficial to be able to analyze and model directly the spatial distributions of cells in histopathology whole slide images (WSI). However, most existing WSI datasets lack cell-level annotation…
View article: From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba
From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Open
Histopathology plays a critical role in medical diagnostics, with whole slide images (WSIs) offering valuable insights that directly influence clinical decision-making. However, the large size and complexity of WSIs may pose significant ch…
View article: Development and validation of AI delineation of the thoracic RTOG organs at risk with deep learning on multi-institutional datasets
Development and validation of AI delineation of the thoracic RTOG organs at risk with deep learning on multi-institutional datasets Open
View article: Leveraging Semantic Asymmetry for Precise Gross Tumor Volume Segmentation of Nasopharyngeal Carcinoma in Planning CT
Leveraging Semantic Asymmetry for Precise Gross Tumor Volume Segmentation of Nasopharyngeal Carcinoma in Planning CT Open
In the radiation therapy of nasopharyngeal carcinoma (NPC), clinicians typically delineate the gross tumor volume (GTV) using non-contrast planning computed tomography to ensure accurate radiation dose delivery. However, the low contrast b…
View article: Low-Rank Continual Pyramid Vision Transformer: Incrementally Segment Whole-Body Organs in CT with Light-Weighted Adaptation
Low-Rank Continual Pyramid Vision Transformer: Incrementally Segment Whole-Body Organs in CT with Light-Weighted Adaptation Open
Deep segmentation networks achieve high performance when trained on specific datasets. However, in clinical practice, it is often desirable that pretrained segmentation models can be dynamically extended to enable segmenting new organs wit…
View article: RevSAM2: Prompt SAM2 for Medical Image Segmentation via Reverse-Propagation without Fine-tuning
RevSAM2: Prompt SAM2 for Medical Image Segmentation via Reverse-Propagation without Fine-tuning Open
The Segment Anything Model 2 (SAM2) has recently demonstrated exceptional performance in zero-shot prompt segmentation for natural images and videos. However, when the propagation mechanism of SAM2 is applied to medical images, it often re…
View article: End-to-end Multi-source Visual Prompt Tuning for Survival Analysis in Whole Slide Images
End-to-end Multi-source Visual Prompt Tuning for Survival Analysis in Whole Slide Images Open
Survival analysis using pathology images poses a considerable challenge, as it requires the localization of relevant information from the multitude of tiles within whole slide images (WSIs). Current methods typically resort to a two-stage …
View article: Effective Lymph Nodes Detection in CT Scans Using Location Debiased Query Selection and Contrastive Query Representation in Transformer
Effective Lymph Nodes Detection in CT Scans Using Location Debiased Query Selection and Contrastive Query Representation in Transformer Open
Lymph node (LN) assessment is a critical, indispensable yet very challenging task in the routine clinical workflow of radiology and oncology. Accurate LN analysis is essential for cancer diagnosis, staging, and treatment planning. Finding …
View article: Vessel and Airway Characteristics in One-Year Computed Tomography–defined Rapid Emphysema Progression: SPIROMICS
Vessel and Airway Characteristics in One-Year Computed Tomography–defined Rapid Emphysema Progression: SPIROMICS Open
Rationale: Rates of emphysema progression vary in chronic obstructive pulmonary disease (COPD), and the relationships with vascular and airway pathophysiology remain unclear. Objectives: We sought to determine if indices of p…
View article: Towards a Comprehensive, Efficient and Promptable Anatomic Structure Segmentation Model using 3D Whole-body CT Scans
Towards a Comprehensive, Efficient and Promptable Anatomic Structure Segmentation Model using 3D Whole-body CT Scans Open
Segment anything model (SAM) demonstrates strong generalization ability on natural image segmentation. However, its direct adaptation in medical image segmentation tasks shows significant performance drops. It also requires an excessive nu…
View article: Modality-Agnostic Structural Image Representation Learning for Deformable Multi-Modality Medical Image Registration
Modality-Agnostic Structural Image Representation Learning for Deformable Multi-Modality Medical Image Registration Open
Establishing dense anatomical correspondence across distinct imaging modalities is a foundational yet challenging procedure for numerous medical image analysis studies and image-guided radiotherapy. Existing multi-modality image registrati…
View article: Multi-site, Multi-domain Airway Tree Modeling
Multi-site, Multi-domain Airway Tree Modeling Open
View article: Anatomy-Aware Lymph Node Detection in Chest CT using Implicit Station Stratification
Anatomy-Aware Lymph Node Detection in Chest CT using Implicit Station Stratification Open
Finding abnormal lymph nodes in radiological images is highly important for various medical tasks such as cancer metastasis staging and radiotherapy planning. Lymph nodes (LNs) are small glands scattered throughout the body. They are group…
View article: SAMConvex: Fast Discrete Optimization for CT Registration using Self-supervised Anatomical Embedding and Correlation Pyramid
SAMConvex: Fast Discrete Optimization for CT Registration using Self-supervised Anatomical Embedding and Correlation Pyramid Open
Estimating displacement vector field via a cost volume computed in the feature space has shown great success in image registration, but it suffers excessive computation burdens. Moreover, existing feature descriptors only extract local fea…
View article: Matching in the Wild: Learning Anatomical Embeddings for Multi-Modality Images
Matching in the Wild: Learning Anatomical Embeddings for Multi-Modality Images Open
Radiotherapists require accurate registration of MR/CT images to effectively use information from both modalities. In a typical registration pipeline, rigid or affine transformations are applied to roughly align the fixed and moving images…
View article: LViT: Language Meets Vision Transformer in Medical Image Segmentation
LViT: Language Meets Vision Transformer in Medical Image Segmentation Open
Deep learning has been widely used in medical image segmentation and other aspects. However, the performance of existing medical image segmentation models has been limited by the challenge of obtaining sufficient high-quality labeled data …
View article: Accurate Airway Tree Segmentation in CT Scans via Anatomy-aware Multi-class Segmentation and Topology-guided Iterative Learning
Accurate Airway Tree Segmentation in CT Scans via Anatomy-aware Multi-class Segmentation and Topology-guided Iterative Learning Open
Intrathoracic airway segmentation in computed tomography (CT) is a prerequisite for various respiratory disease analyses such as chronic obstructive pulmonary disease (COPD), asthma and lung cancer. Unlike other organs with simpler shapes …
View article: Multi-site, Multi-domain Airway Tree Modeling (ATM'22): A Public Benchmark for Pulmonary Airway Segmentation
Multi-site, Multi-domain Airway Tree Modeling (ATM'22): A Public Benchmark for Pulmonary Airway Segmentation Open
Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach of pulmonary airway segmentation that is closer to the limit…
View article: Continual Segment: Towards a Single, Unified and Accessible Continual Segmentation Model of 143 Whole-body Organs in CT Scans
Continual Segment: Towards a Single, Unified and Accessible Continual Segmentation Model of 143 Whole-body Organs in CT Scans Open
Deep learning empowers the mainstream medical image segmentation methods. Nevertheless current deep segmentation approaches are not capable of efficiently and effectively adapting and updating the trained models when new incremental segmen…
View article: Comprehensive and clinically accurate head and neck cancer organs-at-risk delineation on a multi-institutional study
Comprehensive and clinically accurate head and neck cancer organs-at-risk delineation on a multi-institutional study Open
Accurate organ-at-risk (OAR) segmentation is critical to reduce radiotherapy complications. Consensus guidelines recommend delineating over 40 OARs in the head-and-neck (H&N). However, prohibitive labor costs cause most institutions to del…
View article: Towards automated organs at risk and target volumes contouring: Defining precision radiation therapy in the modern era
Towards automated organs at risk and target volumes contouring: Defining precision radiation therapy in the modern era Open
View article: LViT: Language meets Vision Transformer in Medical Image Segmentation
LViT: Language meets Vision Transformer in Medical Image Segmentation Open
Deep learning has been widely used in medical image segmentation and other aspects. However, the performance of existing medical image segmentation models has been limited by the challenge of obtaining sufficient high-quality labeled data …
View article: Deep Implicit Statistical Shape Models for 3D Medical Image Delineation
Deep Implicit Statistical Shape Models for 3D Medical Image Delineation Open
3D delineation of anatomical structures is a cardinal goal in medical imaging analysis. Prior to deep learning, statistical shape models (SSMs) that imposed anatomical constraints and produced high quality surfaces were a core technology. …
View article: Editorial: Machine Learning for Quantitative Neuroimaging Analysis
Editorial: Machine Learning for Quantitative Neuroimaging Analysis Open
EDITORIAL article Front. Neurosci., 25 May 2022Sec. Brain Imaging Methods https://doi.org/10.3389/fnins.2022.925819