Marijn F. Stollenga, Wonmin Byeon, Marcus Liwicki, Juergen Schmidhuber
Convolutional Neural Networks (CNNs) can be shifted across 2D images or 3D videos to segment them. They have a fixed input size and typically perceive only small local contexts of the pixels to be classified as foreground or background. In contrast, Multi-Dimensional Recurrent NNs (MD-RNNs) can perceive the entire spatio-temporal context of each pixel in […]
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Alexander Ortenberg
Parallelization is the answer to the ever-growing demands of computing power by taking advantage of multi-core processor technology and modern many-core graphics compute units. Multi-core CPUs and many-core GPUs have the potential to substantially reduce the execution time of a program but it is often a challenging task to ensure that all available hardware is […]
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Olaf Ronneberger, Philipp Fischer, Thomas Brox
There is large consent that successful training of deep networks requires many thousand annotated training samples. In this paper, we present a network and training strategy that relies on the strong use of data augmentation to use the available annotated samples more efficiently. The architecture consists of a contracting path to capture context and a […]
Reza Nakhjavani
The ever increasing complexity of scientific applications has led to utilization of new HPC paradigms such as Graphical Processing Units (GPUs). However, modifying applications to run on GPU is challenging. Furthermore, the speedup achieved by using GPUs has added a huge heterogeneity to HPC clusters. In this dissertation, we enabled NPAIRS, a neuro-imaging application, to […]
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Holger R. Roth, Amal Farag, Le Lu, Evrim B. Turkbey, Ronald M. Summers
Automatic organ segmentation is an important prerequisite for many computer-aided diagnosis systems. The high anatomical variability of organs in the abdomen, such as the pancreas, prevents many segmentation methods from achieving high accuracies when compared to other segmentation of organs like the liver, heart or kidneys. Recently, the availability of large annotated training sets and […]
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Tianren Wang, Yun Jing
This paper presents a numerical study on a fast marching method based back projection reconstruction algorithm for photoacoustic tomography in heterogeneous media. Transcranial imaging is used here as a case study. To correct for the phase aberration from the heterogeneity (i.e., skull), the fast marching method is adopted to compute the phase delay based on […]
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Albert Haque
Cardiac dysrhythmia is responsible for over half a million deaths in the United States annually. In this work, we evaluate the performance of neural networks on classifying electrocardiogram (ECG) sequences as normal or abnormal (arrhythmia). Using neural networks as our primary learning model, we explain our model’s performance and discuss hyperparameter tuning. Comparing the results […]
Thomas Kovac
As multiple sclerosis is known to cause atrophy and deformation in the brain, it also influences the shape and size of the corpus callosum. Longitudinal studies try to quantify these changes using medical image analysis techniques for measuring and analyzing the shape and size of a corpus callosum cross-sechtion embedded in a specially selected measurement […]
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Seongjin Park, Jeongjin Lee, Hyunna Lee, Juneseuk Shin, Jinwook Seo, Kyoung Ho Lee, Yeong-Gil Shin, Bohyoung Kim
This paper presents a novel method for parallelizing the seeded region growing (SRG) algorithm using Compute Unified Device Architecture (CUDA) technology, with intent to overcome the theoretical weakness of SRG algorithm of its computation time being directly proportional to the size of a segmented region. The segmentation performance of the proposed CUDA-based SRG is compared […]
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M. Leeser, S. Mukherjee, J. Brock
Biomedical image reconstruction applications require producing high fidelity images in or close to real-time. We have implemented reconstruction of three dimensional conebeam computed tomography(CBCT) with two dimensional projections. The algorithm takes slices of the target, weights and filters them to backproject the data, then creates the final 3D volume. We have implemented the algorithm using […]
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Yangping Wang, Lian Li, Jianwu Dang, Chong Deng, Xiaogang Du
Dose Volume Histogram(DVH) is necessary for evaluating radiotherapy planning. With the increase of patient CT slices and the development of intensity-modulated radiation therapy(IMRT) technology, statistical process of DVH requires a large number of cubic interpolation calculation, and the sequential single threaded DVH code on the CPU can not meet the real-time requirement. The paper presents […]
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Christos G Xanthis, Ioannis E Venetis, Anthony H Aletras
BACKGROUND: MRI physics simulators have been developed in the past for optimizing imaging protocols and for training purposes. However, these simulators have only addressed motion within a limited scope. The purpose of this study was the incorporation of realistic motion, such as cardiac motion, respiratory motion and flow, within MRI simulations in a high performance […]
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