Automatic arterial input function selection in CT and MR perfusion datasets using deep convolutional neural networks
نویسندگان
چکیده
منابع مشابه
Automatic Tagging Using Deep Convolutional Neural Networks
We present a content-based automatic music tagging algorithm using fully convolutional neural networks (FCNs). We evaluate different architectures consisting of 2D convolutional layers and subsampling layers only. In the experiments, we measure the AUC-ROC scores of the architectures with different complexities and input types using the MagnaTagATune dataset, where a 4-layer architecture shows ...
متن کاملCystoscopy Image Classication Using Deep Convolutional Neural Networks
In the past three decades, the use of smart methods in medical diagnostic systems has attractedthe attention of many researchers. However, no smart activity has been provided in the eld ofmedical image processing for diagnosis of bladder cancer through cystoscopy images despite the highprevalence in the world. In this paper, two well-known convolutional neural networks (CNNs) ...
متن کاملAutomatic calculation of the arterial input function for cerebral perfusion imaging with MR imaging.
An automated method for determination of arterial input function (AIF) for rapid determination of cerebral perfusion with dynamic susceptibility contrast magnetic resonance (MR) imaging was derived. In 100 patients, the automated method was used to create images of relative blood flow, relative cerebral blood volume, and mean transit time. In 20 patients, the voxel chosen with the automated AIF...
متن کاملEstimation of Hand Skeletal Postures by Using Deep Convolutional Neural Networks
Hand posture estimation attracts researchers because of its many applications. Hand posture recognition systems simulate the hand postures by using mathematical algorithms. Convolutional neural networks have provided the best results in the hand posture recognition so far. In this paper, we propose a new method to estimate the hand skeletal posture by using deep convolutional neural networks. T...
متن کاملAutomatic Segmentation of Liver Tumor in CT Images with Deep Convolutional Neural Networks
Liver tumors segmentation from computed tomography (CT) images is an essential task for diagnosis and treatments of liver cancer. However, it is difficult owing to the variability of appearances, fuzzy boundaries, heterogeneous densities, shapes and sizes of lesions. In this paper, an automatic method based on convolutional neural networks (CNNs) is presented to segment lesions from CT images. ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Medical Physics
سال: 2020
ISSN: 0094-2405,2473-4209
DOI: 10.1002/mp.14351