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標題: Titlebook: Computer-Assisted and Robotic Endoscopy; Third International Terry Peters,Guang-Zhong Yang,Jonathan McLeod Conference proceedings 2017 Spr [打印本頁]

作者: BOUT    時間: 2025-3-21 16:27
書目名稱Computer-Assisted and Robotic Endoscopy影響因子(影響力)




書目名稱Computer-Assisted and Robotic Endoscopy影響因子(影響力)學(xué)科排名




書目名稱Computer-Assisted and Robotic Endoscopy網(wǎng)絡(luò)公開度




書目名稱Computer-Assisted and Robotic Endoscopy網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computer-Assisted and Robotic Endoscopy被引頻次




書目名稱Computer-Assisted and Robotic Endoscopy被引頻次學(xué)科排名




書目名稱Computer-Assisted and Robotic Endoscopy年度引用




書目名稱Computer-Assisted and Robotic Endoscopy年度引用學(xué)科排名




書目名稱Computer-Assisted and Robotic Endoscopy讀者反饋




書目名稱Computer-Assisted and Robotic Endoscopy讀者反饋學(xué)科排名





作者: 火海    時間: 2025-3-21 20:56
The European Community and ASEAN,acy according to overlap size. In contrast to the conventional mosaicking approach, the proposed approach can produce panoramic image even in the case of 0% inter-cameras overlap. Additionally, the proposed approach is fast enough for clinical use.
作者: instate    時間: 2025-3-22 04:13

作者: 記憶    時間: 2025-3-22 04:48
Toussaint Houeninvo,Philippe Sèdédjiution to extend ORBSLAM to be able to reconstruct a semi-dense map of soft organs. Experimental results on in-vivo pigs, shows a robust endoscope tracking even with organs deformations and partial instrument occlusions. It also shows the reconstruction density, and accuracy against ground truth surface obtained from CT.
作者: 起波瀾    時間: 2025-3-22 10:19
Preoperative Diagnostic Procedures,y deep learning, achieves a balanced accuracy of 89.6% on a real clinical dataset, outperforming the (non-real-time) state of the art by 3.8% points. The latter, a combination of deep learning with optical flow tracking, yields an average balanced accuracy of 78.2% across all the validated datasets.
作者: Transfusion    時間: 2025-3-22 14:57

作者: Transfusion    時間: 2025-3-22 19:02

作者: CLASP    時間: 2025-3-22 22:35

作者: 鳴叫    時間: 2025-3-23 03:03
ORBSLAM-Based Endoscope Tracking and 3D Reconstruction,ution to extend ORBSLAM to be able to reconstruct a semi-dense map of soft organs. Experimental results on in-vivo pigs, shows a robust endoscope tracking even with organs deformations and partial instrument occlusions. It also shows the reconstruction density, and accuracy against ground truth surface obtained from CT.
作者: 諂媚于性    時間: 2025-3-23 06:05
Real-Time Segmentation of Non-rigid Surgical Tools Based on Deep Learning and Tracking,y deep learning, achieves a balanced accuracy of 89.6% on a real clinical dataset, outperforming the (non-real-time) state of the art by 3.8% points. The latter, a combination of deep learning with optical flow tracking, yields an average balanced accuracy of 78.2% across all the validated datasets.
作者: APRON    時間: 2025-3-23 13:02
Eleonora Solari,Andrea Moriondo the classification of celiac disease. We will show that the deeper CNN architectures outperform these comparison approaches and that combining CNNs with linear support vector machines furtherly improves the classification rates for about 3–7% leading to distinctly better results (up?to 97%) than those of the comparison methods.
作者: 淺灘    時間: 2025-3-23 15:51
Convolutional Neural Network Architectures for the Automated Diagnosis of Celiac Disease, the classification of celiac disease. We will show that the deeper CNN architectures outperform these comparison approaches and that combining CNNs with linear support vector machines furtherly improves the classification rates for about 3–7% leading to distinctly better results (up?to 97%) than those of the comparison methods.
作者: resilience    時間: 2025-3-23 19:12
Conference proceedings 201713 initial submissions. The papers are organized on topical secttion?such as computer vision, graphics, robotics, medical imaging, external tracking systems, medical device controls systems, information processing techniques, endoscopy planning and simulation..
作者: 收藏品    時間: 2025-3-23 22:11

作者: Lacunar-Stroke    時間: 2025-3-24 04:23
0302-9743 hop on Computer Assisted and Robotic Endoscopy, CARE 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016.. .The 11 revised full papers were carefully selected out of 13 initial submissions. The papers are organized on topical secttion?such as computer vision, graphics, rob
作者: palliate    時間: 2025-3-24 09:57
Toussaint Houeninvo,Philippe Sèdédjiscopy image classification. Experiments on a three class (abnormal, normal, uninformative) white-light colonoscopy image dataset with 2800 images show that the proposed feature perform better than popular hand-designed features used in the medical as well as in the computer vision literature for image classification.
作者: palliate    時間: 2025-3-24 13:40
Extended Multi-resolution Local Patterns - A Discriminative Feature Learning Approach for Colonoscoscopy image classification. Experiments on a three class (abnormal, normal, uninformative) white-light colonoscopy image dataset with 2800 images show that the proposed feature perform better than popular hand-designed features used in the medical as well as in the computer vision literature for image classification.
作者: COW    時間: 2025-3-24 17:41
Conference proceedings 2017opy, CARE 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016.. .The 11 revised full papers were carefully selected out of 13 initial submissions. The papers are organized on topical secttion?such as computer vision, graphics, robotics, medical imaging, external tracking s
作者: 祖?zhèn)?nbsp;   時間: 2025-3-24 21:06

作者: creditor    時間: 2025-3-24 23:28

作者: NOMAD    時間: 2025-3-25 04:20

作者: 使無效    時間: 2025-3-25 09:13

作者: 紅潤    時間: 2025-3-25 15:09

作者: Sad570    時間: 2025-3-25 17:11
Terry Peters,Guang-Zhong Yang,Jonathan McLeodIncludes supplementary material:
作者: 雄辯    時間: 2025-3-25 20:17
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/234468.jpg
作者: discord    時間: 2025-3-26 01:34
On the Biomechanics of External Fixationion of Deep Learning on these data. Convolutional Neural Networks (CNN’s) can be used to enable the extraction of highly representative features among the network layers filtering, selecting and using these features in the last fully connected layers for pattern classification. However, CNN training
作者: Communicate    時間: 2025-3-26 06:03

作者: 發(fā)酵    時間: 2025-3-26 08:27

作者: 都相信我的話    時間: 2025-3-26 14:23

作者: motor-unit    時間: 2025-3-26 17:31

作者: 衰弱的心    時間: 2025-3-27 00:15
The External Sector of Africa‘s Economy polyps during endoscopic sessions. Here, we investigate the impact of enhanced imaging technologies on the classification accuracy of computer-aided diagnosis systems. Specifically, we determine if image representations obtained from different imaging modalities are significantly different and expe
作者: Glower    時間: 2025-3-27 02:24

作者: Nutrient    時間: 2025-3-27 07:13
Preoperative Diagnostic Procedures,lly Convolutional Networks (FCN) and optical flow tracking. Our method exploits the ability of deep neural networks to produce accurate segmentations of highly deformable parts along with the high speed of optical flow. Furthermore, the pre-trained FCN can be fine-tuned on a small amount of medical
作者: 最初    時間: 2025-3-27 10:40
https://doi.org/10.1007/978-3-7091-2058-3ntestinal tract than conventional endoscopy technologies. Despite of the technological advances in this field, the reviewing of the large VCE image sequences remains manual and challenges experts’ diagnostic capabilities. Video reviewing systems for automated lesion detection are still under investi
作者: probate    時間: 2025-3-27 15:37
Eleonora Solari,Andrea Moriondo duodenum. To evaluate which network configurations are best suited for the classification of celiac disease, several different CNN networks were trained using different numbers of layers and filters and different filter dimensions. The results of the CNNs are compared with the results of popular ge
作者: Malleable    時間: 2025-3-27 19:43
https://doi.org/10.1007/978-3-030-99708-3 vessels. This can be achieved by registering pre-operative 3D data such as CT or MRI with the laparoscope’s live video. For soft organs this is very challenging, and quantitative evaluation is both difficult and limited in the literature. It has been done previously by measuring registration accura
作者: Rotator-Cuff    時間: 2025-3-27 22:10

作者: condone    時間: 2025-3-28 03:41

作者: 偽造者    時間: 2025-3-28 06:34

作者: 有節(jié)制    時間: 2025-3-28 11:27
The European Community and ASEAN,e the accuracy and reliability of the tracking and the automatic acquisition. The results indicate a reliable performance of the tracking method. As for automatic acquisition, the mean positioning error in the near field of ultrasound where most structures of clinical interest are located is 10.44?m
作者: 立即    時間: 2025-3-28 18:10
https://doi.org/10.1007/978-3-7091-2058-3nnotation process. It is based on state-of-the-art colour features, which, in this study, are extended according to the bag-of-visual-words model. The area under receiver operating characteristic achieved, reaches 81%.
作者: FISC    時間: 2025-3-28 21:19
https://doi.org/10.1007/978-3-030-99708-3y guide the surgeon, by showing them how to access the tumour with an incision tool. We call this .. Performance was measured with the negative margin rate across 59 resected pseudo-tumours. This was 85.2% with AR guidance and 41.9% without, showing a very significant improvement (., two-tailed Fish
作者: 牛馬之尿    時間: 2025-3-28 23:18

作者: arrhythmic    時間: 2025-3-29 07:04

作者: Nibble    時間: 2025-3-29 07:21
Hybrid Tracking and Matching Algorithm for Mosaicking Multiple Surgical Views,ause of the narrow surgical field of view. To solve this problem, our group proposed camera-retractable trocar which can obtain multiple surgical viewpoints while maintaining the minimally invasiveness. The purpose of this study is to obtain a wide visual panoramic view by utilizing image mosaicking
作者: 諄諄教誨    時間: 2025-3-29 15:05

作者: MAIM    時間: 2025-3-29 16:19
Extended Multi-resolution Local Patterns - A Discriminative Feature Learning Approach for Colonosco-class image classifier. Our approach uses training data with image-level labels to learn the features which are discriminative for multi-class colonoscopy image classification. Experiments on a three class (abnormal, normal, uninformative) white-light colonoscopy image dataset with 2800 images show
作者: negligence    時間: 2025-3-29 20:01

作者: Intentional    時間: 2025-3-30 02:19
ORBSLAM-Based Endoscope Tracking and 3D Reconstruction,e captured by the monocular endoscope. This information offers new possibilities for developing surgical navigation and augmented reality applications. The main benefit of this approach is the lack of extra tracking elements which can disturb the surgeon performance in the clinical routine. It is ou
作者: antidepressant    時間: 2025-3-30 05:32





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