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Deep Lesion Tracker: Monitoring Lesions in 4D Longitudinal Imaging Studies
Monitoring treatment response in longitudinal studies plays an important...
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Self-supervised Learning of Pixel-wise Anatomical Embeddings in Radiological Images
Radiological images such as computed tomography (CT) and X-rays render a...
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One Click Lesion RECIST Measurement and Segmentation on CT Scans
In clinical trials, one of the radiologists' routine work is to measure ...
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E^2Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans
Developing an effective liver and liver tumor segmentation model from CT...
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Cross-Domain Medical Image Translation by Shared Latent Gaussian Mixture Model
Current deep learning based segmentation models often generalize poorly ...
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Bone Suppression on Chest Radiographs With Adversarial Learning
Dual-energy (DE) chest radiography provides the capability of selectivel...
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Weakly Supervised Lesion Co-segmentation on CT Scans
Lesion segmentation in medical imaging serves as an effective tool for a...
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Weakly-Supervised Lesion Segmentation on CT Scans using Co-Segmentation
Lesion segmentation on computed tomography (CT) scans is an important st...
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TUNA-Net: Task-oriented UNsupervised Adversarial Network for Disease Recognition in Cross-Domain Chest X-rays
In this work, we exploit the unsupervised domain adaptation problem for ...
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MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation
When reading medical images such as a computed tomography (CT) scan, rad...
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XLSor: A Robust and Accurate Lung Segmentor on Chest X-Rays Using Criss-Cross Attention and Customized Radiorealistic Abnormalities Generation
This paper proposes a novel framework for lung segmentation in chest X-r...
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Abnormal Chest X-ray Identification With Generative Adversarial One-Class Classifier
Being one of the most common diagnostic imaging tests, chest radiography...
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ULDor: A Universal Lesion Detector for CT Scans with Pseudo Masks and Hard Negative Example Mining
Automatic lesion detection from computed tomography (CT) scans is an imp...
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CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement
Automated lesion segmentation from computed tomography (CT) is an import...
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Accurate Weakly-Supervised Deep Lesion Segmentation using Large-Scale Clinical Annotations: Slice-Propagated 3D Mask Generation from 2D RECIST
Volumetric lesion segmentation from computed tomography (CT) images is a...
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Semi-Automatic RECIST Labeling on CT Scans with Cascaded Convolutional Neural Networks
Response evaluation criteria in solid tumors (RECIST) is the standard me...
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CT-Realistic Lung Nodule Simulation from 3D Conditional Generative Adversarial Networks for Robust Lung Segmentation
Data availability plays a critical role for the performance of deep lear...
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Accurate Weakly Supervised Deep Lesion Segmentation on CT Scans: Self-Paced 3D Mask Generation from RECIST
Volumetric lesion segmentation via medical imaging is a powerful means t...
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Saliency Detection via Combining Region-Level and Pixel-Level Predictions with CNNs
This paper proposes a novel saliency detection method by combining regio...
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Deeply-Supervised Recurrent Convolutional Neural Network for Saliency Detection
This paper proposes a novel saliency detection method by developing a de...
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