Deep learning prostate MRI segmentation accuracy and robustness: a systematic review
Purpose To investigate the accuracy and robustness of prostate segmentation using deep
learning across various training data sizes, MRI vendors, prostate zones, and testing …
learning across various training data sizes, MRI vendors, prostate zones, and testing …
Bridging 2D and 3D segmentation networks for computation-efficient volumetric medical image segmentation: An empirical study of 2.5 D solutions
Y Zhang, Q Liao, L Ding, J Zhang - Computerized Medical Imaging and …, 2022 - Elsevier
Recently, deep convolutional neural networks have achieved great success for medical
image segmentation. However, unlike segmentation of natural images, most medical images …
image segmentation. However, unlike segmentation of natural images, most medical images …
Boundary-weighted domain adaptive neural network for prostate MR image segmentation
Accurate segmentation of the prostate from magnetic resonance (MR) images provides
useful information for prostate cancer diagnosis and treatment. However, automated …
useful information for prostate cancer diagnosis and treatment. However, automated …
Dual-force convolutional neural networks for accurate brain tumor segmentation
S Chen, C Ding, M Liu - Pattern Recognition, 2019 - Elsevier
Brain tumor segmentation from Magnetic Resonance Imaging scans is vital for both the
diagnosis and treatment of brain cancers. It is widely accepted that accurate segmentation …
diagnosis and treatment of brain cancers. It is widely accepted that accurate segmentation …
Quadratic autoencoder (Q-AE) for low-dose CT denoising
Inspired by complexity and diversity of biological neurons, our group proposed quadratic
neurons by replacing the inner product in current artificial neurons with a quadratic …
neurons by replacing the inner product in current artificial neurons with a quadratic …
Deep convolution neural network for big data medical image classification
Deep learning is one of the most unexpected machine learning techniques which is being
used in many applications like image classification, image analysis, clinical archives and …
used in many applications like image classification, image analysis, clinical archives and …
Convolutional neural network with batch normalization for glioma and stroke lesion detection using MRI
Accurate glioma detection using magnetic resonance imaging (MRI) is a complicated job. In
this research, deep learning model is presented for glioma and stroke lesion detection. The …
this research, deep learning model is presented for glioma and stroke lesion detection. The …
Feature fusion encoder decoder network for automatic liver lesion segmentation
X Chen, R Zhang, P Yan - 2019 IEEE 16th international …, 2019 - ieeexplore.ieee.org
Liver lesion segmentation is a difficult yet critical task for medical image analysis. Recently,
deep learning based image segmentation methods have achieved promising performance …
deep learning based image segmentation methods have achieved promising performance …
Recent automatic segmentation algorithms of MRI prostate regions: a review
World-wide incidence rate of prostate cancer has progressively increased with time
especially with the increased proportion of elderly population. Early detection of prostate …
especially with the increased proportion of elderly population. Early detection of prostate …
PSP net-based automatic segmentation network model for prostate magnetic resonance imaging
L Yan, D Liu, Q Xiang, Y Luo, T Wang, D Wu… - Computer Methods and …, 2021 - Elsevier
Purpose: Prostate cancer is a common cancer. To improve the accuracy of early diagnosis,
we propose a prostate Magnetic Resonance Imaging (MRI) segmentation model based on …
we propose a prostate Magnetic Resonance Imaging (MRI) segmentation model based on …