標(biāo)題: Titlebook: Computational Methods and Clinical Applications for Spine Imaging; 4th International Wo Jianhua Yao,Toma? Vrtovec,Shuo Li Conference procee [打印本頁] 作者: whiplash 時(shí)間: 2025-3-21 16:09
書目名稱Computational Methods and Clinical Applications for Spine Imaging影響因子(影響力)
書目名稱Computational Methods and Clinical Applications for Spine Imaging影響因子(影響力)學(xué)科排名
書目名稱Computational Methods and Clinical Applications for Spine Imaging網(wǎng)絡(luò)公開度
書目名稱Computational Methods and Clinical Applications for Spine Imaging網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Computational Methods and Clinical Applications for Spine Imaging被引頻次
書目名稱Computational Methods and Clinical Applications for Spine Imaging被引頻次學(xué)科排名
書目名稱Computational Methods and Clinical Applications for Spine Imaging年度引用
書目名稱Computational Methods and Clinical Applications for Spine Imaging年度引用學(xué)科排名
書目名稱Computational Methods and Clinical Applications for Spine Imaging讀者反饋
書目名稱Computational Methods and Clinical Applications for Spine Imaging讀者反饋學(xué)科排名
作者: Parabola 時(shí)間: 2025-3-21 22:46
What Is Clickbait? (Check All that Apply),east-squares regression. Despite its simplicity and without using specific domain knowledge, our approach achieves sub-voxel localisation accuracy of 0.61?mm, Dice segmentation overlaps of nearly 90% (for the training data) and takes less than ten minutes to process a new scan.作者: 立即 時(shí)間: 2025-3-22 01:26
Michael R. Robinson,Moira M. Fergusonral bodies of the thoracic and lumbar spine. We evaluated osteophyte detection performance on 45 individuals with 5-fold cross validation and achieved state-of-the-art performance with 85% sensitivity at 2 false positive detections per patient.作者: 刻苦讀書 時(shí)間: 2025-3-22 06:22
G. T. O. Lebreton,F. W. (Bill) H. Beamishenerate the patient’s specified 3D model. This method just needs one prior model for 3D reconstruction. The experiments on nine vertebrae of three patients show the average reconstruction error is 1.2?mm (1.0?mm–1.3?mm) which is comparable to the state of the art.作者: Blazon 時(shí)間: 2025-3-22 12:03
Operator Theory: Advances and Applications on Grassmannian kernels in order to assess the similarity between shape topology and inter-vertebral poses in both groups (P, NP). We test the method to classify 52 progressive and 81 non-progressive patients enrolled in a prospective clinical study, yielding classification rates comparing favorably to standard classification methods.作者: CYN 時(shí)間: 2025-3-22 16:50 作者: CYN 時(shí)間: 2025-3-22 21:00
Accurate Intervertebral Disc Localisation and Segmentation in MRI Using Vantage Point Hough Forests east-squares regression. Despite its simplicity and without using specific domain knowledge, our approach achieves sub-voxel localisation accuracy of 0.61?mm, Dice segmentation overlaps of nearly 90% (for the training data) and takes less than ten minutes to process a new scan.作者: condescend 時(shí)間: 2025-3-22 23:19
Detection of Degenerative Osteophytes of the Spine on PET/CT Using Region-Based Convolutional Neuralral bodies of the thoracic and lumbar spine. We evaluated osteophyte detection performance on 45 individuals with 5-fold cross validation and achieved state-of-the-art performance with 85% sensitivity at 2 false positive detections per patient.作者: cutlery 時(shí)間: 2025-3-23 05:18 作者: OTHER 時(shí)間: 2025-3-23 06:11
Classification of Progressive and Non-progressive Scoliosis Patients Using Discriminant Manifolds on Grassmannian kernels in order to assess the similarity between shape topology and inter-vertebral poses in both groups (P, NP). We test the method to classify 52 progressive and 81 non-progressive patients enrolled in a prospective clinical study, yielding classification rates comparing favorably to standard classification methods.作者: rectum 時(shí)間: 2025-3-23 13:13
Molecular Mechanisms in “Stunned” Myocardium vertebrae between T4 and L4 were detected and, of these, 97% were segmented with a mean error of less than or equal to .. A simple classifier was applied to perform a fracture/non-fracture classification for each image, achieving 69% recall at 70% precision.作者: Epidural-Space 時(shí)間: 2025-3-23 14:41 作者: 鑲嵌細(xì)工 時(shí)間: 2025-3-23 20:51
Fully Automatic Localisation of Vertebrae in CT Images Using Random Forest Regression Voting vertebrae between T4 and L4 were detected and, of these, 97% were segmented with a mean error of less than or equal to .. A simple classifier was applied to perform a fracture/non-fracture classification for each image, achieving 69% recall at 70% precision.作者: POLYP 時(shí)間: 2025-3-24 01:44 作者: 有權(quán) 時(shí)間: 2025-3-24 03:08 作者: headlong 時(shí)間: 2025-3-24 07:49
Global Localization and Orientation of the Cervical Spine in X-ray Imagesased voting accumulation method to localize the spinal column and to detect the orientation. The algorithm has been evaluated with 90 emergency room X-ray images and has achieved an average detection accuracy of 91% and an orientation error of 3.6.. The framework can be used to narrow the search area for other advanced injury detection systems.作者: incite 時(shí)間: 2025-3-24 13:38
Fully Automatic Localization and Segmentation of Intervertebral Disc from 3D Multi-modality MR Imageatasets, our method achieved a mean localization distance of 0.64?mm and a mean Dice overlap coefficient of 90.8%. The results show that our method is robust and comparable with state-of-the-art methods.作者: incubus 時(shí)間: 2025-3-24 17:20
Was ist die Biografie eines Menschen?ic classifier. We evaluated the proposed methods on 143 spinal images from two datasets acquired at different sites. We achieved a segmentation recall of 0.9 and precision 0.91 for the better dataset, and a recall and precision of 0.87 and 0.81 for the combined dataset, demonstrating the potential of the framework.作者: 使苦惱 時(shí)間: 2025-3-24 19:17
https://doi.org/10.1007/978-3-319-63751-8ased voting accumulation method to localize the spinal column and to detect the orientation. The algorithm has been evaluated with 90 emergency room X-ray images and has achieved an average detection accuracy of 91% and an orientation error of 3.6.. The framework can be used to narrow the search area for other advanced injury detection systems.作者: gout109 時(shí)間: 2025-3-25 01:08
Vadim J. Birstein,William E. Bemisatasets, our method achieved a mean localization distance of 0.64?mm and a mean Dice overlap coefficient of 90.8%. The results show that our method is robust and comparable with state-of-the-art methods.作者: 追蹤 時(shí)間: 2025-3-25 04:03 作者: 剛開始 時(shí)間: 2025-3-25 07:53
https://doi.org/10.1007/978-3-662-57289-4uous cuts combined with a shape prior. Intensity-based segmentation guarantees high accuracy while the shape prior aims at precision. We tested the algorithm on a set of MR images with visual WM/GM contrast and evaluated it w.r.t. manual GM segmentations. The automated GM segmentations are on a par with the manual results.作者: deciduous 時(shí)間: 2025-3-25 11:58 作者: ANTIC 時(shí)間: 2025-3-25 17:38 作者: CULP 時(shí)間: 2025-3-25 21:22
Automated Intervertebral Disc Segmentation Using Deep Convolutional Neural Networks 2015 IVD segmentation challenge datasets, our method achieved a mean Dice overlap coefficient of 89.2% and a mean average absolute surface distance of 1.3?mm. The results achieved by our method are comparable with those achieved by the state-of-the-art methods.作者: Hdl348 時(shí)間: 2025-3-26 00:30
Conference proceedings 2016Spine Imaging, CSI 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016.. . The 13 workshop papers were carefully reviewed and selected for inclusion in this volume. They aim at reviewing the state-of-the-art techniques, sharing the novel and emerging analysis and visualiza作者: cushion 時(shí)間: 2025-3-26 06:58 作者: Paraplegia 時(shí)間: 2025-3-26 10:11
Jianhua Yao,Toma? Vrtovec,Shuo LiIncludes supplementary material: 作者: Laconic 時(shí)間: 2025-3-26 12:53
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/232690.jpg作者: Malfunction 時(shí)間: 2025-3-26 19:56 作者: 嚴(yán)厲批評(píng) 時(shí)間: 2025-3-27 00:55
978-3-319-55049-7Springer International Publishing AG 2016作者: Musculoskeletal 時(shí)間: 2025-3-27 01:16
Ellen Prang,Irene Gabriel,Helga Schlofferening complications. Computer aided analysis of X-ray images has the potential to detect missed injuries. Segmentation of the vertebrae is a crucial step towards automatic injury detection system. Active shape model (ASM) is one of the most successful and popular method for vertebrae segmentation. I作者: 攤位 時(shí)間: 2025-3-27 09:02 作者: 倔強(qiáng)不能 時(shí)間: 2025-3-27 11:36 作者: bibliophile 時(shí)間: 2025-3-27 16:50
Gestaltung von ?m?nnlichen“ Angebotenigated the influence of four different patch sampling strategies on the performance of the deep convolutional neural networks. Evaluated on the MICCAI 2015 IVD segmentation challenge datasets, our method achieved a mean Dice overlap coefficient of 89.2% and a mean average absolute surface distance o作者: 合唱團(tuán) 時(shí)間: 2025-3-27 18:12 作者: 證實(shí) 時(shí)間: 2025-3-27 22:45 作者: 閑蕩 時(shí)間: 2025-3-28 05:06
What Is Clickbait? (Check All that Apply),discs in MRI is challenging due to the small field of view and repetitive structures, which may cause the image registration to converge to a local minimum. To tackle this initialisation problem, our approach uses . to automatically and robustly regress landmark positions, which are used to initiali作者: 哀悼 時(shí)間: 2025-3-28 09:36 作者: neuron 時(shí)間: 2025-3-28 13:58 作者: carotenoids 時(shí)間: 2025-3-28 18:27
https://doi.org/10.1007/978-3-642-77057-9mensional (3D) computed tomography (CT) images of 17 patients with thoracic spinal deformities. Manual planning was performed by two spine surgeons by means of a dedicated software for planning of surgical procedures, while computer-assisted planning was based on automated 3D segmentation and modeli作者: palliative-care 時(shí)間: 2025-3-28 22:36 作者: 運(yùn)氣 時(shí)間: 2025-3-29 02:48 作者: prodrome 時(shí)間: 2025-3-29 03:28 作者: 尊敬 時(shí)間: 2025-3-29 08:29
Improving an Active Shape Model with Random Classification Forest for Segmentation of Cervical Verteening complications. Computer aided analysis of X-ray images has the potential to detect missed injuries. Segmentation of the vertebrae is a crucial step towards automatic injury detection system. Active shape model (ASM) is one of the most successful and popular method for vertebrae segmentation. I作者: maverick 時(shí)間: 2025-3-29 12:57
Machine Learning Based Bone Segmentation in Ultrasound segmentation from US images remains a challenge due to the low signal to noise ratio and artifacts that hamper US images. We propose to learn the appearance of bone-soft tissue interfaces from annotated training data, and present results with two classifiers, structured forest and a cascaded logist作者: Preserve 時(shí)間: 2025-3-29 19:33
Variational Segmentation of the White and Gray Matter in the Spinal Cord Using a Shape Priorr (WM/GM). We present a variational formulation to automatically detect cerebrospinal fluid and WM/GM. The segmentation results are obtained by continuous cuts combined with a shape prior. Intensity-based segmentation guarantees high accuracy while the shape prior aims at precision. We tested the al作者: 偽造 時(shí)間: 2025-3-29 21:04
Automated Intervertebral Disc Segmentation Using Deep Convolutional Neural Networksigated the influence of four different patch sampling strategies on the performance of the deep convolutional neural networks. Evaluated on the MICCAI 2015 IVD segmentation challenge datasets, our method achieved a mean Dice overlap coefficient of 89.2% and a mean average absolute surface distance o作者: indifferent 時(shí)間: 2025-3-30 03:51 作者: 節(jié)省 時(shí)間: 2025-3-30 07:36
Global Localization and Orientation of the Cervical Spine in X-ray Imagesd analysis of the images has the potential to reduce the chance of missing injuries. Towards this goal, this paper proposes an automatic localization of the spinal column in cervical spine X-ray images. The framework employs a random classification forest algorithm with a kernel density estimation-b作者: CRAFT 時(shí)間: 2025-3-30 09:12
Accurate Intervertebral Disc Localisation and Segmentation in MRI Using Vantage Point Hough Forests discs in MRI is challenging due to the small field of view and repetitive structures, which may cause the image registration to converge to a local minimum. To tackle this initialisation problem, our approach uses . to automatically and robustly regress landmark positions, which are used to initiali
