Medical Image Computing and Computer Assisted Intervention – MICCAI 2019
22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part II
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136 Result(s)
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English
Artificial Intelligence
Pattern Recognition
M. **gliang
Computer Science
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Article
Focus for Free in Density-Based Counting
This work considers supervised learning to count from images and their corresponding point annotations. Where density-based counting methods typically use the point annotations only to create Gaussian-density ...
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Article
Open AccessContext-Driven Detection of Invertebrate Species in Deep-Sea Video
Each year, underwater remotely operated vehicles (ROVs) collect thousands of hours of video of unexplored ocean habitats revealing a plethora of information regarding biodiversity on Earth. However, fully util...
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Article
Fine-Grained Instance-Level Sketch-Based Image Retrieval
The problem of fine-grained sketch-based image retrieval (FG-SBIR) is defined and investigated in this paper. In FG-SBIR, free-hand human sketch images are used as queries to retrieve photo images containing t...
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Chapter and Conference Paper
Over-and-Under Complete Convolutional RNN for MRI Reconstruction
Reconstructing magnetic resonance (MR) images from under-sampled data is a challenging problem due to various artifacts introduced by the under-sampling operation. Recent deep learning-based methods for MR ima...
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Chapter and Conference Paper
Lossless Image Compression Using a Multi-scale Progressive Statistical Model
Lossless image compression is an important technique for image storage and transmission when information loss is not allowed. With the fast development of deep learning techniques, deep neural networks have be...
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Chapter and Conference Paper
Lesion Mask-Based Simultaneous Synthesis of Anatomic and Molecular MR Images Using a GAN
Data-driven automatic approaches have demonstrated their great potential in resolving various clinical diagnostic dilemmas for patients with malignant gliomas in neuro-oncology with the help of conventional an...
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Chapter and Conference Paper
Few Is Enough: Task-Augmented Active Meta-learning for Brain Cell Classification
Deep Neural Networks (or DNNs) must constantly cope with distribution changes in the input data when the task of interest or the data collection protocol changes. Retraining a network from scratch to combat th...
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Chapter and Conference Paper
MR-to-US Registration Using Multiclass Segmentation of Hepatic Vasculature with a Reduced 3D U-Net
Accurate hepatic vessel segmentation and registration using ultrasound (US) can contribute to beneficial navigation during hepatic surgery. However, it is challenging due to noise and speckle in US imaging and...
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Chapter and Conference Paper
Deep Placental Vessel Segmentation for Fetoscopic Mosaicking
During fetoscopic laser photocoagulation, a treatment for twin-to-twin transfusion syndrome (TTTS), the clinician first identifies abnormal placental vascular connections and laser ablates them to regulate blo...
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Article
Synthesis of High-Quality Visible Faces from Polarimetric Thermal Faces using Generative Adversarial Networks
The large domain discrepancy between faces captured in polarimetric (or conventional) thermal and visible domains makes cross-domain face verification a highly challenging problem for human examiners as well a...
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Book and Conference Proceedings
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Book and Conference Proceedings
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019
22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part I
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Book and Conference Proceedings
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019
22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part VI
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Book and Conference Proceedings
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019
22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part V
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Book and Conference Proceedings
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019
22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part IV
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Chapter and Conference Paper
The Sixth Visual Object Tracking VOT2018 Challenge Results
The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers...
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Chapter and Conference Paper
Hydranet: Data Augmentation for Regression Neural Networks
Deep learning techniques are often criticized to heavily depend on a large quantity of labeled data. This problem is even more challenging in medical image analysis where the annotator expertise is often scar...
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Chapter and Conference Paper
Generative Adversarial Network for Segmentation of Motion Affected Neonatal Brain MRI
Automatic neonatal brain tissue segmentation in preterm born infants is a prerequisite for evaluation of brain development. However, automatic segmentation is often hampered by motion artifacts caused by infan...
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Chapter and Conference Paper
Multiple Sclerosis Lesion Segmentation with Tiramisu and 2.5D Stacked Slices
In this paper, we present a fully convolutional densely connected network (Tiramisu) for multiple sclerosis (MS) lesion segmentation. Different from existing methods, we use stacked slices from all three anato...
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Chapter and Conference Paper
Optimal Experimental Design for Biophysical Modelling in Multidimensional Diffusion MRI
Computational models of biophysical tissue properties have been widely used in diffusion MRI (dMRI) research to elucidate the link between microstructural properties and MR signal formation. For brain tissue,...
