Multi-sequence MR generated sCT is promising for HNC MR-only RT: a comprehensive evaluation of previously developed sCT generation networks.
Sign Up to like & getrecommendations! Published in 2022 at "Medical physics"
DOI: 10.1002/mp.15572
Abstract: PURPOSE To verify the feasibility of our in-house developed multi-sequence magnetic resonance (MR)-generated synthetic computed tomography (sCT) for the accurate dose calculation and fractional positioning for head and neck MR-only radiation therapy (RT). MATERIALS AND… read more here.
Keywords: generated sct; evaluation; sequence; image ... See more keywords
Postoperative glioma segmentation in CT image using deep feature fusion model guided by multi-sequence MRIs
Sign Up to like & getrecommendations! Published in 2019 at "European Radiology"
DOI: 10.1007/s00330-019-06441-z
Abstract: Objectives Computed tomography (CT) and magnetic resonance imaging (MRI) are the most commonly selected methods for imaging gliomas. Clinically, radiotherapists always delineate the CT glioma region with reference to multi-modal MR image information. On this… read more here.
Keywords: multi sequence; postoperative glioma; segmentation; guided multi ... See more keywords
Modified local ternary patterns technique for brain tumour segmentation and volume estimation from MRI multi-sequence scans with GPU CUDA machine
Sign Up to like & getrecommendations! Published in 2019 at "Biocybernetics and Biomedical Engineering"
DOI: 10.1016/j.bbe.2019.02.002
Abstract: Abstract The proposed work develops a rapid and automatic method for brain tumour detection and segmentation using multi-sequence magnetic resonance imaging (MRI) datasets available from BraTS. The proposed method consists of three phases: tumourous slice… read more here.
Keywords: ternary patterns; method; volume estimation; local ternary ... See more keywords
Feasibility of synthetic computed tomography generated with an adversarial network for multi-sequence magnetic resonance-based brain radiotherapy
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Radiation Research"
DOI: 10.1093/jrr/rrz063
Abstract: ABSTRACT The aim of this work is to generate synthetic computed tomography (sCT) images from multi-sequence magnetic resonance (MR) images using an adversarial network and to assess the feasibility of sCT-based treatment planning for brain… read more here.
Keywords: adversarial network; multi sequence; feasibility; radiotherapy ... See more keywords
Ensemble learning-based radiomics with multi-sequence magnetic resonance imaging for benign and malignant soft tissue tumor differentiation
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DOI: 10.1371/journal.pone.0286417
Abstract: Many previous studies focused on differentiating between benign and malignant soft tissue tumors using radiomics model based on various magnetic resonance imaging (MRI) sequences, but it is still unclear how to set up the input… read more here.
Keywords: soft tissue; sequence; benign malignant; multi sequence ... See more keywords
Radiomics models based on multi-sequence MRI for preoperative evaluation of MUC4 status in pancreatic ductal adenocarcinoma: a preliminary study
Sign Up to like & getrecommendations! Published in 2022 at "Quantitative Imaging in Medicine and Surgery"
DOI: 10.21037/qims-22-112
Abstract: Background Mucin 4 (MUC4) overexpression promotes tumorigenesis and increases the aggressiveness of pancreatic ductal adenocarcinoma (PDAC). To date, no study has reported the association between radiomics and MUC4 expression in PDAC. Thus, we aimed to… read more here.
Keywords: based multi; expression; multi sequence; mri ... See more keywords
Multi-Sequence MR-Based Radiomics Signature for Predicting Early Recurrence in Solitary Hepatocellular Carcinoma ≤5 cm
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Oncology"
DOI: 10.3389/fonc.2022.899404
Abstract: Purpose To investigate the value of radiomics features derived from preoperative multi-sequence MR images for predicting early recurrence (ER) in patients with solitary hepatocellular carcinoma (HCC) ≤5 cm. Methods One hundred and ninety HCC patients… read more here.
Keywords: predicting early; clinical radiological; multi sequence; radiomics features ... See more keywords
Predicting IDH Mutation Status in Low-Grade Gliomas Based on Optimal Radiomic Features Combined with Multi-Sequence Magnetic Resonance Imaging
Sign Up to like & getrecommendations! Published in 2022 at "Diagnostics"
DOI: 10.3390/diagnostics12122995
Abstract: The IDH somatic mutation status is an important basis for the diagnosis and classification of gliomas. We proposed a “6-Step” general radiomics model to noninvasively predict the IDH mutation status by simultaneously tuning combined multi-sequence… read more here.
Keywords: idh mutation; multi sequence; mutation status;
Single and Multi-Sequence Deep Learning Models for Short and Medium Term Electric Load Forecasting
Sign Up to like & getrecommendations! Published in 2019 at "Energies"
DOI: 10.3390/en12010149
Abstract: Time series analysis using long short term memory (LSTM) deep learning is a very attractive strategy to achieve accurate electric load forecasting. Although it outperforms most machine learning approaches, the LSTM forecasting model still reveals… read more here.
Keywords: time; multi sequence; electric load; load ... See more keywords
Early brainstem hemorrhage progression: multi-sequence magnetic resonance imaging and histopathology
Sign Up to like & getrecommendations! Published in 2022 at "Neural Regeneration Research"
DOI: 10.4103/1673-5374.344838
Abstract: [INLINE:1] According to clinical statistics, the mortality of patients with early brainstem hemorrhage is high. In this study, we established rat models of brainstem hemorrhage by injecting type VII collagenase into the right basotegmental pontine… read more here.
Keywords: brainstem hemorrhage; histopathology; multi sequence; early brainstem ... See more keywords