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08/10/2023
Leverage Weakly Annotation to Pixel-wise Annotation via Zero-shot Segment Anything Model for Molecular-empowered Learning
Precise identification of multiple cell classes in high-resolution Giga-...
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08/10/2023
High-performance Data Management for Whole Slide Image Analysis in Digital Pathology
When dealing with giga-pixel digital pathology in whole-slide imaging, a...
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07/31/2023
Disruptive Autoencoders: Leveraging Low-level features for 3D Medical Image Pre-training
Harnessing the power of pre-training on large-scale datasets like ImageN...
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07/03/2023
Feasibility of Universal Anomaly Detection without Knowing the Abnormality in Medical Images
Many anomaly detection approaches, especially deep learning methods, hav...
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07/01/2023
All-in-SAM: from Weak Annotation to Pixel-wise Nuclei Segmentation with Prompt-based Finetuning
The Segment Anything Model (SAM) is a recently proposed prompt-based seg...
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05/31/2023
Democratizing Pathological Image Segmentation with Lay Annotators via Molecular-empowered Learning
Multi-class cell segmentation in high-resolution Giga-pixel whole slide ...
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05/16/2023
Annotating 8,000 Abdominal CT Volumes for Multi-Organ Segmentation in Three Weeks
Annotating medical images, particularly for organ segmentation, is labor...
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04/09/2023
Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging
The segment anything model (SAM) was released as a foundation model for ...
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01/02/2023
CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection
An increasing number of public datasets have shown a marked clinical imp...
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11/04/2022
MONAI: An open-source framework for deep learning in healthcare
Artificial Intelligence (AI) is having a tremendous impact across most a...
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09/04/2022
Time-distance vision transformers in lung cancer diagnosis from longitudinal computed tomography
Features learned from single radiologic images are unable to provide inf...
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06/17/2022
A Comparative Study of Confidence Calibration in Deep Learning: From Computer Vision to Medical Imaging
Although deep learning prediction models have been successful in the dis...
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06/02/2022
Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives
Transformer, the latest technological advance of deep learning, has gain...
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05/12/2022
Pseudo-Label Guided Multi-Contrast Generalization for Non-Contrast Organ-Aware Segmentation
Non-contrast computed tomography (NCCT) is commonly acquired for lung ca...
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03/04/2022
Characterizing Renal Structures with 3D Block Aggregate Transformers
Efficiently quantifying renal structures can provide distinct spatial co...
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01/04/2022
Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images
Semantic segmentation of brain tumors is a fundamental medical image ana...
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11/29/2021
Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis
Vision Transformers (ViT)s have shown great performance in self-supervis...
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09/18/2021
Random Multi-Channel Image Synthesis for Multiplexed Immunofluorescence Imaging
Multiplex immunofluorescence (MxIF) is an emerging imaging technique tha...
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07/27/2021
Technical Report: Quality Assessment Tool for Machine Learning with Clinical CT
Image Quality Assessment (IQA) is important for scientific inquiry, espe...
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07/25/2021
Lung Cancer Risk Estimation with Incomplete Data: A Joint Missing Imputation Perspective
Data from multi-modality provide complementary information in clinical p...
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06/03/2021
Attention-Guided Supervised Contrastive Learning for Semantic Segmentation
Contrastive learning has shown superior performance in embedding global ...
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12/23/2020
Multi-Contrast Computed Tomography Healthy Kidney Atlas
The construction of three-dimensional multi-modal tissue maps provides a...
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12/23/2020
RAP-Net: Coarse-to-Fine Multi-Organ Segmentation with Single Random Anatomical Prior
Performing coarse-to-fine abdominal multi-organ segmentation facilitates...
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12/05/2020
Development and Characterization of a Chest CT Atlas
A major goal of lung cancer screening is to identify individuals with pa...
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10/19/2020
Deep Multi-path Network Integrating Incomplete Biomarker and Chest CT Data for Evaluating Lung Cancer Risk
Clinical data elements (CDEs) (e.g., age, smoking history), blood marker...
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02/10/2020
Validation and Optimization of Multi-Organ Segmentation on Clinical Imaging Archives
Segmentation of abdominal computed tomography(CT) provides spatial conte...
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02/10/2020
Outlier Guided Optimization of Abdominal Segmentation
Abdominal multi-organ segmentation of computed tomography (CT) images ha...
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12/16/2019
Internal-transfer Weighting of Multi-task Learning for Lung Cancer Detection
Recently, multi-task networks have shown to both offer additional estima...
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12/01/2019
Stochastic tissue window normalization of deep learning on computed tomography
Tissue window filtering has been widely used in deep learning for comput...
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11/14/2019
Contrast Phase Classification with a Generative Adversarial Network
Dynamic contrast enhanced computed tomography (CT) is an imaging techniq...
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11/12/2019
Deep Multi-task Prediction of Lung Cancer and Cancer-free Progression from Censored Heterogenous Clinical Imaging
Annual low dose computed tomography (CT) lung screening is currently adv...
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11/12/2019
Semi-Supervised Multi-Organ Segmentation through Quality Assurance Supervision
Human in-the-loop quality assurance (QA) is typically performed after me...
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09/11/2019
Distanced LSTM: Time-Distanced Gates in Long Short-Term Memory Models for Lung Cancer Detection
The field of lung nodule detection and cancer prediction has been rapidl...
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07/15/2019
Enabling Multi-Shell b-Value Generalizability of Data-Driven Diffusion Models with Deep SHORE
Abstract. Intra-voxel models of the diffusion signal are essential for i...
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12/09/2018