Synseg-net: Synthetic segmentation without target modality ground truth
A key limitation of deep convolutional neural network (DCNN)-based image segmentation
methods is the lack of generalizability. Manually traced training images are typically required …
methods is the lack of generalizability. Manually traced training images are typically required …
Adversarial synthesis learning enables segmentation without target modality ground truth
A lack of generalizability is one key limitation of deep learning based segmentation.
Typically, one manually labels new training images when segmenting organs in different …
Typically, one manually labels new training images when segmenting organs in different …
Smart pathological brain detection by synthetic minority oversampling technique, extreme learning machine, and Jaya algorithm
YD Zhang, G Zhao, J Sun, X Wu, ZH Wang… - Multimedia Tools and …, 2018 - Springer
Pathological brain detection is an automated computer-aided diagnosis for brain images.
This study provides a novel method to achieve this goal. We first used synthetic minority …
This study provides a novel method to achieve this goal. We first used synthetic minority …
Towards portable large-scale image processing with high-performance computing
High-throughput, large-scale medical image computing demands tight integration of high-
performance computing (HPC) infrastructure for data storage, job distribution, and image …
performance computing (HPC) infrastructure for data storage, job distribution, and image …
Exploring a smart pathological brain detection method on pseudo Zernike moment
YD Zhang, Y Jiang, W Zhu, S Lu, G Zhao - Multimedia Tools and …, 2018 - Springer
Pathological brain detection by computer vision is now attracting intense attentions from
academic fields. Nevertheless, most of recent methods suffer from low-accuracy. This study …
academic fields. Nevertheless, most of recent methods suffer from low-accuracy. This study …
A comparison of intracranial volume estimation methods and their cross‐sectional and longitudinal associations with age
S Nerland, TS Stokkan, KN Jørgensen… - Human Brain …, 2022 - Wiley Online Library
Intracranial volume (ICV) is frequently used in volumetric magnetic resonance imaging (MRI)
studies, both as a covariate and as a variable of interest. Findings of associations between …
studies, both as a covariate and as a variable of interest. Findings of associations between …
Quantitative assessment of field strength, total intracranial volume, sex, and age effects on the goodness of harmonization for volumetric analysis on the ADNI …
When analyzing large multicenter databases, the effects of multiple confounding covariates
increase the variability in the data and may reduce the ability to detect changes due to the …
increase the variability in the data and may reduce the ability to detect changes due to the …
Volumetric segmentation in the context of posterior fossa-related pathologies: a systematic review
Background Segmentation tools continue to advance, evolving from manual contouring to
deep learning. Researchers have utilized segmentation to study a myriad of posterior fossa …
deep learning. Researchers have utilized segmentation to study a myriad of posterior fossa …
Cat swarm optimization applied to alcohol use disorder identification
Abstract (Aim) Alcohol use disorder may put health at risk and cause serious health
problems. It is of increasing importance to identify alcohol use disorder as early as …
problems. It is of increasing importance to identify alcohol use disorder as early as …
[PDF][PDF] RETRACTED: Multiple Sclerosis Recognition by Biorthogonal Wavelet Features and Fitness-Scaled Adaptive Genetic Algorithm
Aim: Multiple sclerosis (MS) is a disease, which can affect the brain and/or spinal cord,
leading to a wide range of potential symptoms. This method aims to propose a novel MS …
leading to a wide range of potential symptoms. This method aims to propose a novel MS …