標(biāo)題: Titlebook: Computational Methods and Clinical Applications for Spine Imaging; 6th International Wo Yunliang Cai,Liansheng Wang,Shuo Li Conference proc [打印本頁] 作者: HEIR 時(shí)間: 2025-3-21 19:01
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: Blemish 時(shí)間: 2025-3-22 00:05 作者: Organization 時(shí)間: 2025-3-22 03:49 作者: ARBOR 時(shí)間: 2025-3-22 07:45 作者: PUT 時(shí)間: 2025-3-22 11:50 作者: 開始沒有 時(shí)間: 2025-3-22 16:45 作者: 開始沒有 時(shí)間: 2025-3-22 19:28
Sturm-Liouville Theory and its Applicationsal compromise. Quantitative measures from vertebral body segmentations from Computed Tomography (CT) scans have been useful for assessing fracture risk predictions and vertebrae stability. Previous segmentation methods used to generate these metrics were slow and required manual intervention, limiti作者: 勛章 時(shí)間: 2025-3-23 01:05 作者: 迫擊炮 時(shí)間: 2025-3-23 04:35 作者: ENNUI 時(shí)間: 2025-3-23 07:53 作者: 門閂 時(shí)間: 2025-3-23 12:49
Springer Undergraduate Mathematics Seriesthe bounding box of each vertebra followed by a HR-Net to refine the keypoint detections. In Method-2, we implement a similar two-stage system, which firstly extract 68 rough points along the spine curves using a Simple Baseline. We then generate patches and make sure each of them contains three ver作者: 壟斷 時(shí)間: 2025-3-23 16:51
Springer Undergraduate Mathematics Seriestworks focusing on segmentation and regression, respectively. Based on the results generated by the segmentation model, the regression network directly predicts the cobb angles from segmentation masks. To alleviate the domain shift problem appeared between training and testing sets, we also conduct 作者: 南極 時(shí)間: 2025-3-23 19:00 作者: Proclaim 時(shí)間: 2025-3-23 22:30 作者: Genteel 時(shí)間: 2025-3-24 04:11 作者: 格言 時(shí)間: 2025-3-24 09:12 作者: liposuction 時(shí)間: 2025-3-24 11:39 作者: Nefarious 時(shí)間: 2025-3-24 16:48
Spectral Theory in the Singular Casengles is time-consuming, and the results are also heavily affected by the expert’s choice. In this paper, we propose a spine curve guide framework to directly regress the cobb angle from single AP view X-rays images. We firstly design a segmentation network to accurately segment two spine boundary, 作者: 非秘密 時(shí)間: 2025-3-24 20:28
Spectral Theory in the Singular Caseuming and unreliable, automated estimation has been more and more popular. But it remains to be such a great challenge that direct estimation has poor precision due to the lack of information. To meet this challenge, we propose a Multi-Task learning method with pyramidal feature aggregation. Our met作者: 譏笑 時(shí)間: 2025-3-25 01:10 作者: progestogen 時(shí)間: 2025-3-25 04:39 作者: 擦試不掉 時(shí)間: 2025-3-25 11:27
A Coarse-to-Fine Deep Heatmap Regression Method for Adolescent Idiopathic Scoliosis Assessmentis paper, we propose an automatic detection method for AIS assessment from X-ray CT images. Our deep learning based coarse-to-fine heatmaps regression method achieves symmetric mean absolute percentage error (SMAPE) of 24.7987 in the grand challenge AASCE 2019.作者: 偉大 時(shí)間: 2025-3-25 13:18 作者: conservative 時(shí)間: 2025-3-25 15:58 作者: monologue 時(shí)間: 2025-3-25 21:01
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/232691.jpg作者: aptitude 時(shí)間: 2025-3-26 02:11 作者: 是突襲 時(shí)間: 2025-3-26 07:41 作者: 阻礙 時(shí)間: 2025-3-26 08:29
Self-Adjoint Boundary Problems,ion, we participated in the international challenge “Accurate Automated Spinal Curvature Estimation, MICCAI 2019” (100 scans). On the challenge’s test set, we obtained an average symmetric mean absolute percentage error of 22.96.作者: Insufficient 時(shí)間: 2025-3-26 14:15 作者: condone 時(shí)間: 2025-3-26 17:31
Detection of Vertebral Fractures in CT Using 3D Convolutional Neural Networks database of 90 cases that has been semi-automatically generated using radiologist readings that are readily available in clinical practice. Our 3D method produces an Area Under the Curve (AUC) of 95% for patient-level fracture detection and an AUC of 93% for vertebra-level fracture detection in a five-fold cross-validation experiment.作者: poliosis 時(shí)間: 2025-3-26 22:37
Automated Estimation of the Spinal Curvature via Spine Centerline Extraction with Ensembles of Cascaion, we participated in the international challenge “Accurate Automated Spinal Curvature Estimation, MICCAI 2019” (100 scans). On the challenge’s test set, we obtained an average symmetric mean absolute percentage error of 22.96.作者: legislate 時(shí)間: 2025-3-27 03:55
Automated Spinal Curvature Assessment from X-Ray Images Using Landmarks Estimation Network via Rotat proposals are co-registered and fed into stage-two fully convoluted network (FCN) for vertebrate landmarks detection. The performance of proposed method is more robust than traditional landmarks segmentation networks for datasets with large variance, with a SMAPE score of 25.4784.作者: goodwill 時(shí)間: 2025-3-27 07:01
Sturm-Liouville Theory and its Applicationso test the generalization ability of the two trained networks. Research results show that the segmentation performance of semi-cGAN and fewshot-GAN is slightly superior to 3D U-Net for automatic segmenting lumbosacral structures on thin-layer CT with fewer labeled data.作者: Duodenitis 時(shí)間: 2025-3-27 10:28
Springer Undergraduate Mathematics Series in numbers. A delicate postprocess of clustering is proposed to deal with dense keypoint predictions due to the freedom of patch selections. After fusing Method-1 and Method-2, we achieve competitive results on the public leaderboard of AASCE2019 challenge.作者: Relinquish 時(shí)間: 2025-3-27 14:43 作者: Expand 時(shí)間: 2025-3-27 21:26
Spectral Theory in the Singular Caseformation, we make the fusion of the pyramidal features and extend the base model by adding an extra branch for spinal segmentation. We evaluate our method on the validation set from the challenge (Accurate Automated Spinal Curvature Estimation, MICCAI 2019) and obtain a symmetric mean absolute percentage error of 12.97.作者: Alpha-Cells 時(shí)間: 2025-3-27 23:00 作者: alcoholism 時(shí)間: 2025-3-28 03:50
Accurate Automated Keypoint Detections for Spinal Curvature Estimation in numbers. A delicate postprocess of clustering is proposed to deal with dense keypoint predictions due to the freedom of patch selections. After fusing Method-1 and Method-2, we achieve competitive results on the public leaderboard of AASCE2019 challenge.作者: 雪白 時(shí)間: 2025-3-28 06:30 作者: Chameleon 時(shí)間: 2025-3-28 11:50
A Multi-task Learning Method for Direct Estimation of Spinal Curvatureformation, we make the fusion of the pyramidal features and extend the base model by adding an extra branch for spinal segmentation. We evaluate our method on the validation set from the challenge (Accurate Automated Spinal Curvature Estimation, MICCAI 2019) and obtain a symmetric mean absolute percentage error of 12.97.作者: 聲音刺耳 時(shí)間: 2025-3-28 15:54 作者: nepotism 時(shí)間: 2025-3-28 20:04
Springer Undergraduate Mathematics Seriesy predicts the cobb angles from segmentation masks. To alleviate the domain shift problem appeared between training and testing sets, we also conduct a domain adaptation module into network structures. Finally, by ensembling the predictions of different models, our method achieves . SMAPE in the testing set.作者: Coeval 時(shí)間: 2025-3-29 00:37 作者: 泛濫 時(shí)間: 2025-3-29 04:39
Seg4Reg Networks for Automated Spinal Curvature Estimationy predicts the cobb angles from segmentation masks. To alleviate the domain shift problem appeared between training and testing sets, we also conduct a domain adaptation module into network structures. Finally, by ensembling the predictions of different models, our method achieves . SMAPE in the testing set.作者: murmur 時(shí)間: 2025-3-29 07:46 作者: 粗語 時(shí)間: 2025-3-29 14:28
Conditioned Variational Auto-encoder for Detecting Osteoporotic Vertebral Fracturesighing regime that maximizes the classification yield. Furthermore, we ‘look into’ the learnt network by investigating the saliency maps, traversing the latent space and demonstrating its smoothness. Finally, we report our results on two datasets, including the publicly available xVertSeg dataset achieving an F1 score of 84%.作者: 墊子 時(shí)間: 2025-3-29 18:44 作者: medieval 時(shí)間: 2025-3-29 23:44 作者: 痛苦一生 時(shí)間: 2025-3-30 01:22 作者: Lament 時(shí)間: 2025-3-30 06:26 作者: FLORA 時(shí)間: 2025-3-30 09:41
Spectral Theory in the Singular Caseand then aggregate the obtained boundary scoremap with the original spinal X-rays images to input another angle estimation network to make high-precision regression prediction for cobb angle. We evaluate our method in the AASCE19 challenge, and our result achieves 22.1775 SMAPE that shows strong competitiveness compared to other excellent methods.作者: 抗體 時(shí)間: 2025-3-30 14:01
Detection of Vertebral Fractures in CT Using 3D Convolutional Neural Networksdictors for secondary osteoporotic fractures. We present a detection method to opportunistically screen spine-containing CT images for the presence of these vertebral fractures. Inspired by radiology practice, existing methods are based on 2D and 2.5D features but we present, to the best of our know作者: 沉著 時(shí)間: 2025-3-30 17:06 作者: 流浪 時(shí)間: 2025-3-30 21:29 作者: 混亂生活 時(shí)間: 2025-3-31 01:10
Vertebral Labelling in Radiographs: Learning a Coordinate Corrector to Enforce Spinal Shapeowever, due to tissue overlaying and size of spinal radiographs, vertebrae localization and labeling are challenging and complicated. To address this, we propose a robust approach for landmark detection in large and noisy images and apply it on spinal radiographs. In this approach, the model has a h作者: motor-unit 時(shí)間: 2025-3-31 06:04
