| ²é¿´: 316 | »Ø¸´: 5 | ||
| ±¾Ìû²úÉú 1 ¸ö £¬µã»÷ÕâÀï½øÐв鿴 | ||
| µ±Ç°Ö»ÏÔʾÂú×ãÖ¸¶¨Ìõ¼þµÄ»ØÌû£¬µã»÷ÕâÀï²é¿´±¾»°ÌâµÄËùÓлØÌû | ||
pxm_neuÌú³æ (ÖøÃûдÊÖ)
|
[ÇóÖú]
Çó¼ìË÷ÊÕ¼ºÅ
|
|
|
Intelligent Robotics and Applications Volume 9244 of the series Lecture Notes in Computer Science pp 455-461 Date: 20 August 2015 Emphysema Classification Using Convolutional Neural Networks Xiaomin Pei Çó¼ìË÷ÊÕ¼ºÅ£¬Ä¿Ç°ÔÚhttps://link.springer.com/chapter/10.1007%2F978-3-319-22879-2_42ÒѾÄܲ鵽ÁË |
» ²ÂÄãϲ»¶
Ò»Ö¾Ô¸Î÷°²½»Í¨´óѧ²ÄÁϹ¤³Ìרҵ 282·ÖÇóµ÷¼Á
ÒѾÓÐ11È˻ظ´
269ר˶Çóµ÷¼Á
ÒѾÓÐ3È˻ظ´
×ÊÔ´Óë»·¾³ µ÷¼ÁÉêÇë(333·Ö)
ÒѾÓÐ3È˻ظ´
²ÄÁÏÇóµ÷¼Á
ÒѾÓÐ5È˻ظ´
354Çóµ÷¼Á
ÒѾÓÐ9È˻ظ´
»¯Ñ§¹¤³Ì321·ÖÇóµ÷¼Á
ÒѾÓÐ22È˻ظ´
¿¼Ñе÷¼Á
ÒѾÓÐ3È˻ظ´
326Çóµ÷¼Á
ÒѾÓÐ8È˻ظ´
333Çóµ÷¼Á
ÒѾÓÐ7È˻ظ´
Ò»Ö¾Ô¸¶«»ª´óѧ¿ØÖÆÑ§Ë¶320Çóµ÷¼Á
ÒѾÓÐ3È˻ظ´

pxm_neu
Ìú³æ (ÖøÃûдÊÖ)
- Ó¦Öú: 0 (Ó×¶ùÔ°)
- ½ð±Ò: 13.5
- É¢½ð: 320
- ºì»¨: 4
- Ìû×Ó: 1399
- ÔÚÏß: 184.8Сʱ
- ³æºÅ: 695585
- ×¢²á: 2009-02-03
- ÐÔ±ð: MM
- רҵ: µç×ÓѧÓëÐÅϢϵͳ

4Â¥2016-01-12 18:25:43
lazy½õϪ
°æÖ÷ (ÖªÃû×÷¼Ò)
- Ó¦Öú: 155 (¸ßÖÐÉú)
- ¹ó±ö: 2.371
- ½ð±Ò: 26118.4
- É¢½ð: 15360
- ºì»¨: 180
- ɳ·¢: 15
- Ìû×Ó: 5537
- ÔÚÏß: 1929.5Сʱ
- ³æºÅ: 2046157
- ×¢²á: 2012-10-06
- ÐÔ±ð: GG
- רҵ: ¹¦ÄÜÓëÖÇÄܸ߷Ö×Ó
- ¹ÜϽ: ¼ìË÷֪ʶ
¡¾´ð°¸¡¿Ó¦Öú»ØÌû
¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï
¸Ðл²ÎÓ룬ӦÖúÖ¸Êý +1
pxm_neu: ½ð±Ò+10, ллÁË 2016-01-12 20:08:51
Ðľ²_ÒÀÈ»: LS-EPI+1, ¸ÐлӦÖú 2016-01-13 09:44:33
¸Ðл²ÎÓ룬ӦÖúÖ¸Êý +1
pxm_neu: ½ð±Ò+10, ллÁË 2016-01-12 20:08:51
Ðľ²_ÒÀÈ»: LS-EPI+1, ¸ÐлӦÖú 2016-01-13 09:44:33
|
Emphysema Classification Using Convolutional Neural Networks ×÷Õß ei, XM (Pei, Xiaomin)±àÕß:Liu, H; Kubota, N; Zhu, X; Dillmann, R; Zhou, D INTELLIGENT ROBOTICS AND APPLICATIONS, ICIRA 2015, PT I ´ÔÊé: Lecture Notes in Artificial Intelligence ¾í: 9244 Ò³: 455-461 DOI: 10.1007/978-3-319-22879-2_42 ³ö°æÄê: 2015 ²é¿´ÆÚ¿¯ÐÅÏ¢ »áÒéÃû³Æ »áÒé: 8th International Conference on Intelligent Robotics and Applications (ICIRA) »áÒ鵨µã: Portsmouth, ENGLAND »áÒéÈÕÆÚ: AUG 24-27, 2015 ÕªÒª There has been paid more and more attention in diagnosing emphysema using High-resolution Computed Tomography. This may lead to improve both understanding and computer-aided diagnosis. We propose a novel classification framework using convolutional neural network(CNN). This model automatically extracts features from the raw image and generates classification. Experiments have been conducted on the database from clinical. Results a recognition rate of 92.54% for classification two kinds of emphysema with normal. The designed convolutional neural networks can get better results for classifying one kind of emphysema with normal. ¹Ø¼ü´Ê ×÷Õ߹ؼü´Ê:High-resolution computed tomography; Emphysema; Convolutional neural network KeyWords Plus:COMPUTED-TOMOGRAPHY; PULMONARY-EMPHYSEMA; QUANTIFICATION; IMAGES; COPD ×÷ÕßÐÅÏ¢ ͨѶ×÷ÕßµØÖ·: Pei, XM (ͨѶ×÷Õß) [ÏÔʾÔöÇ¿×éÖ¯ÐÅÏ¢µÄÃû³Æ] Liaoning Shihua Univ, Coll Informat & Control Engn, Fushun, Peoples R China. µØÖ·: [ÏÔʾÔöÇ¿×éÖ¯ÐÅÏ¢µÄÃû³Æ] [ 1 ] Liaoning Shihua Univ, Coll Informat & Control Engn, Fushun, Peoples R China µç×ÓÓʼþµØÖ·:pxm_neu@126.com ³ö°æÉÌ SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY Àà±ð / ·ÖÀà Ñо¿·½Ïò:Automation & Control Systems; Computer Science; Robotics Web of Science Àà±ð:Automation & Control Systems; Computer Science, Artificial Intelligence; Computer Science, Interdisciplinary Applications; Robotics ÎÄÏ×ÐÅÏ¢ ÎÄÏ×ÀàÐÍ roceedings PaperÓïÖÖ:English Èë²ØºÅ: WOS:000364714000042 ISBN:978-3-319-22879-2; 978-3-319-22878-5 ISSN: 0302-9743 ÆäËûÐÅÏ¢ IDS ºÅ: BD9IC Web of Science ºËÐĺϼ¯ÖÐµÄ "ÒýÓõIJο¼ÎÄÏ×": 23 Web of Science ºËÐĺϼ¯ÖÐµÄ "±»ÒýƵ´Î": 0 |
2Â¥2016-01-12 18:11:44
lazy½õϪ
°æÖ÷ (ÖªÃû×÷¼Ò)
- Ó¦Öú: 155 (¸ßÖÐÉú)
- ¹ó±ö: 2.371
- ½ð±Ò: 26118.4
- É¢½ð: 15360
- ºì»¨: 180
- ɳ·¢: 15
- Ìû×Ó: 5537
- ÔÚÏß: 1929.5Сʱ
- ³æºÅ: 2046157
- ×¢²á: 2012-10-06
- ÐÔ±ð: GG
- רҵ: ¹¦ÄÜÓëÖÇÄܸ߷Ö×Ó
- ¹ÜϽ: ¼ìË÷֪ʶ
3Â¥2016-01-12 18:11:56
lazy½õϪ
°æÖ÷ (ÖªÃû×÷¼Ò)
- Ó¦Öú: 155 (¸ßÖÐÉú)
- ¹ó±ö: 2.371
- ½ð±Ò: 26118.4
- É¢½ð: 15360
- ºì»¨: 180
- ɳ·¢: 15
- Ìû×Ó: 5537
- ÔÚÏß: 1929.5Сʱ
- ³æºÅ: 2046157
- ×¢²á: 2012-10-06
- ÐÔ±ð: GG
- רҵ: ¹¦ÄÜÓëÖÇÄܸ߷Ö×Ó
- ¹ÜϽ: ¼ìË÷֪ʶ
5Â¥2016-01-12 19:19:22













»Ø¸´´ËÂ¥
ei, XM (Pei, Xiaomin)