Tissue segmentation‐based electron density mapping for MR‐only radiotherapy treatment planning of brain using conventional T1‐weighted MR images
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Applied Clinical Medical Physics"
DOI: 10.1002/acm2.12654
Abstract: Abstract Purpose Magnetic resonance imaging (MRI) is the primary modality for targeting brain tumors in radiotherapy treatment planning (RTP). MRI is not directly used for dose calculation since image voxel intensities of MRI are not… read more here.
Keywords: treatment planning; tissue; radiotherapy treatment; tissue segmentation ... See more keywords
Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging
Sign Up to like & getrecommendations! Published in 2018 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.26841
Abstract: To describe and evaluate a new fully automated musculoskeletal tissue segmentation method using deep convolutional neural network (CNN) and three‐dimensional (3D) simplex deformable modeling to improve the accuracy and efficiency of cartilage and bone segmentation… read more here.
Keywords: segmentation; magnetic resonance; deep convolutional; convolutional neural ... See more keywords
Gadolinium effect on thalamus and whole brain tissue segmentation
Sign Up to like & getrecommendations! Published in 2018 at "Neuroradiology"
DOI: 10.1007/s00234-018-2082-5
Abstract: PurposeGadolinium-based contrast agent (GBCA) effect on automated segmentation algorithms of subcortical gray matter (GM) is not fully known. The aim of this study is to determine gadolinium effect on the segmentation of the thalamus and… read more here.
Keywords: brain tissue; segmentation; tissue; effect ... See more keywords
Liver tissue segmentation in multiphase CT scans using cascaded convolutional neural networks
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Computer Assisted Radiology and Surgery"
DOI: 10.1007/s11548-019-01989-z
Abstract: PurposeWe address the automatic segmentation of healthy and cancerous liver tissues (parenchyma, active and necrotic parts of hepatocellular carcinoma (HCC) tumor) on multiphase CT images using a deep learning approach.MethodsWe devise a cascaded convolutional neural… read more here.
Keywords: liver tissue; cascaded convolutional; segmentation; convolutional neural ... See more keywords
Abstract ID: 114 The impact of dual-energy CT tissue segmentation for low-dose rate prostate brachytherapy Monte Carlo dose calculations
Sign Up to like & getrecommendations! Published in 2017 at "Physica Medica"
DOI: 10.1016/j.ejmp.2017.09.061
Abstract: Purpose To evaluate the impact of a novel tissue segmentation method based on dual-energy CT (DECT) for low-dose rate (LDR) brachytherapy dose calculations, by comparison with a reference single-energy CT (SECT) segmentation method. Methods A… read more here.
Keywords: energy; segmentation; tissue; geometry ... See more keywords
Automated tissue segmentation of MR brain images in the presence of white matter lesions
Sign Up to like & getrecommendations! Published in 2017 at "Medical Image Analysis"
DOI: 10.1016/j.media.2016.08.014
Abstract: &NA; Over the last few years, the increasing interest in brain tissue volume measurements on clinical settings has led to the development of a wide number of automated tissue segmentation methods. However, white matter lesions… read more here.
Keywords: automated tissue; segmentation; tissue; tissue segmentation ... See more keywords
Quantitative Analysis of Patch-Based Fully Convolutional Neural Networks for Tissue Segmentation on Brain Magnetic Resonance Imaging
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2926697
Abstract: Accurate brain tissue segmentation in magnetic resonance imaging (MRI) has attracted the attention of medical doctors and researchers since variations in tissue volume and shape permit diagnosing and monitoring neurological diseases. Several proposals have been… read more here.
Keywords: patch; resonance imaging; magnetic resonance; segmentation ... See more keywords
Unsupervised Tissue Segmentation via Deep Constrained Gaussian Network
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2022.3195123
Abstract: Tissue segmentation is the mainstay of pathological examination, whereas the manual delineation is unduly burdensome. To assist this time-consuming and subjective manual step, researchers have devised methods to automatically segment structures in pathological images. Recently,… read more here.
Keywords: tissue segmentation; segmentation; gaussian network; constrained gaussian ... See more keywords
Histopathological Tissue Segmentation of Lung Cancer with Bilinear CNN and Soft Attention
Sign Up to like & getrecommendations! Published in 2022 at "BioMed Research International"
DOI: 10.1155/2022/7966553
Abstract: Automatic tissue segmentation in whole-slide images (WSIs) is a critical task in hematoxylin and eosin- (H&E-) stained histopathological images for accurate diagnosis and risk stratification of lung cancer. Patch classification and stitching the classification results… read more here.
Keywords: tissue segmentation; lung cancer; bilinear cnn; cancer ... See more keywords
Fully Automated Wound Tissue Segmentation Using Deep Learning on Mobile Devices: Cohort Study.
Sign Up to like & getrecommendations! Published in 2022 at "JMIR mHealth and uHealth"
DOI: 10.2196/36977
Abstract: BACKGROUND Composition of tissue types within a wound is a useful indicator of its healing progression. Tissue composition is clinically used in wound healing tools (eg, Bates-Jensen Wound Assessment Tool) to assess risk and recommend… read more here.
Keywords: study; wound tissue; tissue; wound ... See more keywords
Breast Dense Tissue Segmentation with Noisy Labels: A Hybrid Threshold-Based and Mask-Based Approach
Sign Up to like & getrecommendations! Published in 2022 at "Diagnostics"
DOI: 10.3390/diagnostics12081822
Abstract: Breast density assessed from digital mammograms is a known biomarker related to a higher risk of developing breast cancer. Supervised learning algorithms have been implemented to determine this. However, the performance of these algorithms depends… read more here.
Keywords: breast; tissue segmentation; segmentation; threshold based ... See more keywords