Deformable Model-Based Segmentation of Brain Tumor from MR Images

Extraction of Metastatic Lymph Nodes from MR Images Using Two Deformable Model-based Approaches

Journal of Digital Imaging ◽

10.1007/s10278-006-1037-2 ◽

2007 ◽

Vol 20 (4) ◽

pp. 336-346 ◽

Cited By ~ 3

Author(s):

Jia-Yin Zhou ◽

Wen Fang ◽

Kap-Luk Chan ◽

Vincent F. H. Chong ◽

James B. K. Khoo

Keyword(s):

Lymph Nodes ◽

Deformable Model ◽

Mr Images ◽

Metastatic Lymph Nodes ◽

Model Based ◽

Metastatic Lymph

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A New Method for the Registration of Cardiac PET and MR Images Using Deformable Model Based Segmentation of the Main Thorax Structures

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001 - Lecture Notes in Computer Science ◽

10.1007/3-540-45468-3_67 ◽

2001 ◽

pp. 557-564 ◽

Cited By ~ 9

Author(s):

Timo Mäkelä ◽

Patrick Clarysse ◽

Jyrki Lötjönen ◽

Outi Sipilä ◽

Kirsi Lauerma ◽

...

Keyword(s):

Deformable Model ◽

New Method ◽

Cardiac Pet ◽

Mr Images ◽

Model Based

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Model Library for Deformable Model-Based Segmentation of 3-D Brain MR-Images

Medical Image Computing and Computer-Assisted Intervention — MICCAI 2002 - Lecture Notes in Computer Science ◽

10.1007/3-540-45786-0_67 ◽

2002 ◽

pp. 540-547 ◽

Cited By ~ 4

Author(s):

Juha Koikkalainen ◽

Jyrki Lötjönen

Keyword(s):

Deformable Model ◽

Mr Images ◽

Model Based ◽

Model Library ◽

Brain Mr Images

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A deformable model-based minimal path segmentation method for kidney MR images

10.1117/12.772347 ◽

2008 ◽

Cited By ~ 1

Author(s):

Ke Li ◽

Baowei Fei

Keyword(s):

Deformable Model ◽

Segmentation Method ◽

Mr Images ◽

Minimal Path ◽

Model Based ◽

Path Segmentation

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Statistical textural feature and deformable model based MR brain tumor segmentation

2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI) ◽

10.1109/icacci.2016.7732121 ◽

2016 ◽

Cited By ~ 4

Author(s):

Shoaib Amin Banday ◽

Ajaz Hussain Mir

Keyword(s):

Brain Tumor ◽

Deformable Model ◽

Tumor Segmentation ◽

Textural Feature ◽

Brain Tumor Segmentation ◽

Model Based ◽

Mr Brain

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Statistical textural feature and deformable model based brain tumor segmentation and volume estimation

Multimedia Tools and Applications ◽

10.1007/s11042-016-3979-9 ◽

2016 ◽

Vol 76 (3) ◽

pp. 3809-3828 ◽

Cited By ~ 9

Author(s):

Shoaib Amin Banday ◽

Ajaz Hussain Mir

Keyword(s):

Brain Tumor ◽

Volume Estimation ◽

Deformable Model ◽

Tumor Segmentation ◽

Textural Feature ◽

Brain Tumor Segmentation ◽

Model Based

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An Advanced Approach for Extraction of Brain Tumor from Digital MR Images Using Morphology Gradient & ART

International Review on Computers and Software (IRECOS) ◽

10.15866/irecos.v10i6.6255 ◽

2015 ◽

Vol 10 (6) ◽

pp. 566

Author(s):

Abderrahim Khatabi ◽

Amal Tmiri ◽

Ahmed Serhir

Keyword(s):

Brain Tumor ◽

Mr Images

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An Efficient Hybrid Approach for Brain Tumor Detection in MR Images using Hadoop-MapReduce

2020 International Conferences on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics) ◽

10.1109/ithings-greencom-cpscom-smartdata-cybermatics50389.2020.00144 ◽

2020 ◽

Author(s):

Prabhjot Kaur Chahal ◽

Shreelekha Pandey

Keyword(s):

Brain Tumor ◽

Hybrid Approach ◽

Tumor Detection ◽

Mr Images ◽

Hadoop Mapreduce

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Combining variational and model-based techniques to register PET and MR images in hand osteoarthritis

Physics in Medicine and Biology ◽

10.1088/0031-9155/55/16/009 ◽

2010 ◽

Vol 55 (16) ◽

pp. 4755-4769 ◽

Cited By ~ 9

Author(s):

Derek Magee ◽

Steven F Tanner ◽

Michael Waller ◽

Ai Lyn Tan ◽

Dennis McGonagle ◽

...

Keyword(s):

Hand Osteoarthritis ◽

Mr Images ◽

Model Based

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Content-based brain tumor retrieval for MR images with joint deep and handcrafted visual features

10.1109/dsins54396.2021.9670565 ◽

2021 ◽

Author(s):

Weikang Huang ◽

Wei Zou ◽

Erxi Fang ◽

Nan Hu ◽

Jiajun Wang

Keyword(s):

Brain Tumor ◽

Visual Features ◽

Mr Images

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