Class information for: |
Basic class information |
Class id | #P | Avg. number of references |
Database coverage of references |
---|---|---|---|
8726 | 1224 | 30.8 | 58% |
Hierarchy of classes |
The table includes all classes above and classes immediately below the current class. |
Cluster id | Level | Cluster label | #P |
---|---|---|---|
9 | 4 | COMPUTER SCIENCE, THEORY & METHODS//COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE//COMPUTER SCIENCE, INFORMATION SYSTEMS | 1247339 |
26 | 3 | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE//PATTERN RECOGNITION//COMPUTER SCIENCE, SOFTWARE ENGINEERING | 111824 |
765 | 2 | IMAGE SEGMENTATION//ACTIVE CONTOURS//SEGMENTATION | 12312 |
8726 | 1 | STATISTICAL SHAPE MODEL//ACTIVE SHAPE MODEL//CARDIAC SEGMENTATION | 1224 |
Terms with highest relevance score |
rank | Term | termType | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|---|
1 | STATISTICAL SHAPE MODEL | authKW | 705528 | 5% | 43% | 66 |
2 | ACTIVE SHAPE MODEL | authKW | 496379 | 4% | 36% | 55 |
3 | CARDIAC SEGMENTATION | authKW | 280630 | 1% | 75% | 15 |
4 | POINT DISTRIBUTION MODELS | authKW | 274379 | 2% | 50% | 22 |
5 | LEFT VENTRICLE SEGMENTATION | authKW | 247982 | 1% | 76% | 13 |
6 | MEDICAL IMAGE ANALYSIS | journal | 199236 | 8% | 8% | 95 |
7 | DEFORMABLE MODELS | authKW | 185443 | 5% | 13% | 59 |
8 | IEEE TRANSACTIONS ON MEDICAL IMAGING | journal | 164183 | 13% | 4% | 158 |
9 | CARDIAC IMAGES | authKW | 124728 | 0% | 100% | 5 |
10 | CARDIAC MAGNETIC RESONANCE IMAGE | authKW | 112252 | 0% | 75% | 6 |
Web of Science journal categories |
Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|
1 | Engineering, Biomedical | 39267 | 45% | 0% | 548 |
2 | Radiology, Nuclear Medicine & Medical Imaging | 23913 | 54% | 0% | 658 |
3 | Computer Science, Interdisciplinary Applications | 20938 | 35% | 0% | 432 |
4 | Imaging Science & Photographic Technology | 19603 | 18% | 0% | 220 |
5 | Computer Science, Artificial Intelligence | 13335 | 27% | 0% | 336 |
6 | Computer Science, Theory & Methods | 8466 | 23% | 0% | 284 |
7 | Medical Informatics | 3487 | 7% | 0% | 82 |
8 | Engineering, Electrical & Electronic | 2121 | 26% | 0% | 317 |
9 | Computer Science, Information Systems | 865 | 7% | 0% | 91 |
10 | Computer Science, Software Engineering | 677 | 6% | 0% | 72 |
Address terms |
Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|
1 | MED IMAGE DISPLAY ANAL GRP | 102617 | 1% | 34% | 12 |
2 | DIGITAL IMAGING SYST | 49891 | 0% | 100% | 2 |
3 | GBBA | 49891 | 0% | 100% | 2 |
4 | COMP AIDED DIAG GRP | 44900 | 0% | 60% | 3 |
5 | COMPUTAT IMAGING SIMULAT TECHNOL BIOMED | 42081 | 1% | 19% | 9 |
6 | DIGITAL IMAGING GRP LONDON | 33259 | 0% | 67% | 2 |
7 | GRP INGN BIOMED GIBULA | 33259 | 0% | 67% | 2 |
8 | PROGRAMME ELECT ENGN | 33259 | 0% | 67% | 2 |
9 | VAMC BROCKTON | 33259 | 0% | 67% | 2 |
10 | GIT VIS | 32069 | 0% | 43% | 3 |
Journals |
Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|
1 | MEDICAL IMAGE ANALYSIS | 199236 | 8% | 8% | 95 |
2 | IEEE TRANSACTIONS ON MEDICAL IMAGING | 164183 | 13% | 4% | 158 |
3 | COMPUTERIZED MEDICAL IMAGING AND GRAPHICS | 34849 | 4% | 3% | 49 |
4 | INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY | 31105 | 3% | 3% | 42 |
5 | LECTURE NOTES IN COMPUTER SCIENCE | 15389 | 19% | 0% | 235 |
6 | IMAGE AND VISION COMPUTING | 11167 | 3% | 1% | 34 |
7 | IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE | 4656 | 1% | 1% | 14 |
8 | COMPUTER VISION AND IMAGE UNDERSTANDING | 3641 | 1% | 1% | 17 |
9 | IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING | 3446 | 3% | 0% | 33 |
10 | INTERNATIONAL JOURNAL OF COMPUTER VISION | 3118 | 1% | 1% | 15 |
Author Key Words |
Core articles |
The table includes core articles in the class. The following variables is taken into account for the relevance score of an article in a cluster c: (1) Number of references referring to publications in the class. (2) Share of total number of active references referring to publications in the class. (3) Age of the article. New articles get higher score than old articles. (4) Citation rate, normalized to year. |
Rank | Reference | # ref. in cl. |
Shr. of ref. in cl. |
Citations |
---|---|---|---|---|
1 | DACHER, JN , PETITJEAN, C , (2011) A REVIEW OF SEGMENTATION METHODS IN SHORT AXIS CARDIAC MR IMAGES.MEDICAL IMAGE ANALYSIS. VOL. 15. ISSUE 2. P. 169 -184 | 47 | 72% | 178 |
2 | PENG, P , LEKADIR, K , GOOYA, A , SHAO, L , PETERSEN, SE , FRANGI, AF , (2016) A REVIEW OF HEART CHAMBER SEGMENTATION FOR STRUCTURAL AND FUNCTIONAL ANALYSIS USING CARDIAC MAGNETIC RESONANCE IMAGING.MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE. VOL. 29. ISSUE 2. P. 155 -195 | 74 | 52% | 2 |
3 | HEIMANN, T , MEINZER, HP , (2009) STATISTICAL SHAPE MODELS FOR 3D MEDICAL IMAGE SEGMENTATION: A REVIEW.MEDICAL IMAGE ANALYSIS. VOL. 13. ISSUE 4. P. 543-563 | 54 | 49% | 410 |
4 | TAVAKOLI, V , AMINI, AA , (2013) A SURVEY OF SHAPED-BASED REGISTRATION AND SEGMENTATION TECHNIQUES FOR CARDIAC IMAGES.COMPUTER VISION AND IMAGE UNDERSTANDING. VOL. 117. ISSUE 9. P. 966 -989 | 74 | 50% | 17 |
5 | CARNEIRO, G , NASCIMENTO, JC , (2013) COMBINING MULTIPLE DYNAMIC MODELS AND DEEP LEARNING ARCHITECTURES FOR TRACKING THE LEFT VENTRICLE ENDOCARDIUM IN ULTRASOUND DATA.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE. VOL. 35. ISSUE 11. P. 2592-2607 | 36 | 71% | 16 |
6 | CORDERO-GRANDE, L , VEGAS-SANCHEZ-FERRERO, G , CASASECA-DE-LA-HIGUERA, P , SAN-ROMAN-CALVAR, JA , REVILLA-ORODEA, A , MARTIN-FERNANDEZ, M , ALBEROLA-LOPEZ, C , (2011) UNSUPERVISED 4D MYOCARDIUM SEGMENTATION WITH A MARKOV RANDOM FIELD BASED DEFORMABLE MODEL.MEDICAL IMAGE ANALYSIS. VOL. 15. ISSUE 3. P. 283 -301 | 36 | 64% | 21 |
7 | GOLLMER, ST , KIRSCHNER, M , BUZUG, TM , WESARG, S , (2014) USING IMAGE SEGMENTATION FOR EVALUATING 3D STATISTICAL SHAPE MODELS BUILT WITH GROUPWISE CORRESPONDENCE OPTIMIZATION.COMPUTER VISION AND IMAGE UNDERSTANDING. VOL. 125. ISSUE . P. 283 -303 | 25 | 81% | 2 |
8 | ALBA, X , PEREANEZ, M , HOOGENDOORN, C , SWIFT, AJ , WILD, JM , FRANGI, AF , LEKADIR, K , (2016) AN ALGORITHM FOR THE SEGMENTATION OF HIGHLY ABNORMAL HEARTS USING A GENERIC STATISTICAL SHAPE MODEL.IEEE TRANSACTIONS ON MEDICAL IMAGING. VOL. 35. ISSUE 3. P. 845 -859 | 26 | 74% | 0 |
9 | O'BRIEN, SP , GHITA, O , WHELAN, PF , (2011) A NOVEL MODEL-BASED 3D+TIME LEFT VENTRICULAR SEGMENTATION TECHNIQUE.IEEE TRANSACTIONS ON MEDICAL IMAGING. VOL. 30. ISSUE 2. P. 461 -474 | 24 | 86% | 12 |
10 | WU, YW , WANG, YQ , JIA, YD , (2013) SEGMENTATION OF THE LEFT VENTRICLE IN CARDIAC CINE MRI USING A SHAPE-CONSTRAINED SNAKE MODEL.COMPUTER VISION AND IMAGE UNDERSTANDING. VOL. 117. ISSUE 9. P. 990 -1003 | 26 | 72% | 13 |
Classes with closest relation at Level 1 |