Medical Imaging

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  Automatic Body Part Identification in Whole-Body MRI

  • Published on: October, 2020
  • a-doering
  • Code Available

  The study of medical imaging data from large cohort studies, such as Magnetic Resonance Imaging (MRI), takes a long time. As a result, model for autom ...

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  Image reconstruction by domain-transform manifold learning

  • Published on: March, 2017
  • Bruce R. Rosen, Jeremiah Z. Liu, Matthew S. Rosen, Bo Zhu
  • Code Available

  Magnetic resonance imaging (MRI), X-ray computed tomography (CT), positron emission tomography (PET), ultrasound, and radio astronomy all rely on imag ...

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  Deep CT to MR Synthesis Using Paired and Unpaired Data

  • Published on: May, 2019
  • Wonmo Jung, In Ho Han, Hakil Kim, Xuenan Cui, Cheng-Bin Jin, Jae Il Lee, Seongsu Joo, Mingjie Liu, Eunsik Park...
  • Code Available

  Magnetic resonance (MR) imaging plays a highly important role in radiotherapy treatment planning for the segmentation of tumor volumes and organs. How ...

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  Retina Blood Vessel Segmentation

  • Published on: June, 2018
  • Orobix
  • Code Available

  Retina blood vessel segmentation with a convolution neural network (U-net) takes up the binary classification task to predicts if each pixel in the fu ...

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  Unsupervised Domain Adaptation from Axial to Short-Axis Multi-Slice Cardiac MR Images by Incorporating Pretrained Task Networks

  • Published on: January, 2021
  • Heiner Latus, Ivo Wolf, Tarique Hussain, Samir Sarikouch, Gerald Greil, Florian Ritzmann, Tyler Huffaker, Zach...
  • Code Available

  The model uses Unsupervised Domain Adaptation (UDA) of 3D cardiac magnetic resonance (CMR) images to transform from axial to short-axis orientation an ...

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  Low Dose CT Image Denoising using A Generative Adversarial Network with Wasserstein Distance and Perceptual Loss

  • Published on: April, 2018
  • Mannudeep K. Kalra, Hengyong Yu, Member, Xuanqin Mou, Pingkun Yan, Qingsong Yang, Senior Member, Yi Zhang Memb...
  • Code Available

  The continuous development and extensive use of CT in medical practice has raised a public concern over the associated radiation dose to the patient. ...

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  Hierarchical 3D fully convolutional networks for multi-organ segmentation

  • Published on: April, 2017
  • Michitaka Fujiwara, Holger R. Roth, Hirohisa Oda1, and Kensaku Mori, Masahiro Oda, Natsuki Shimizu, Kazunari M...
  • Code Available

  The model demonstrates how hierarchical deployment of 3D CNN based on a fully convolutional architecture (3D U-Net) can produce competitive results fo ...

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  Co occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation

  • Published on: March, 2019
  • Max Strobel
  • Code Available

  Skeleton-based human action recognition has recently drawn increasing attentions with the availability of large-scale skeleton datasets. The most cruc ...

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  Heart Segmentation From MRI Scans Using Convolutional Neural Network

  • Published on: November, 2019
  • Muhammad Usman, Shakeel Muhammad Ibrahim,  Imran Naseem, Muhammad Sohail Ibrahim, Muhammad Moinuddin
  • Code Available

  Heart is essential organ of human body. For patients having cardiovascular diseases(CVD), it is important to monitor physiology of heart effectively. ...

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  XNet A convolutional neural network CNN implementation for medical XRay image segmentation suitable for small datasets

  • Published on: December, 2018
  • Joseph Aylett-Bullock, Carolina Cuesta, Arnau Quera-Bofarull
  • Code Available

  XNet is a Convolutional Neural Network designed for the segmentation of X-Ray images into bone, soft tissue and open beam regions. Specifically, it pe ...