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3. Small Defect Detection Using Convolutional Neural Network Features and Random Forests

Author

Dong, Xinghui, Taylor, Chris J., Cootes, Tim F., Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Leal-Taixé, Laura, editor, and Roth, Stefan, editor

Published
2019
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5. Learning-Based Shape Model Matching: Training Accurate Models with Minimal Manual Input

Author

Lindner, Claudia, Thomson, Jessie, Consortium, The arcOGEN, Cootes, Tim F., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Navab, Nassir, editor, Hornegger, Joachim, editor, Wells, William M., editor, and Frangi, Alejandro F., editor

Published
2015
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7. Accurate Bone Segmentation in 2D Radiographs Using Fully Automatic Shape Model Matching Based On Regression-Voting

Author

arcOGEN Consortium, Lindner, Claudia, Thiagarajah, Shankar, Wilkinson, J. Mark, Wallis, Gillian A., Cootes, Tim F., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Mori, Kensaku, editor, Sakuma, Ichiro, editor, Sato, Yoshinobu, editor, Barillot, Christian, editor, and Navab, Nassir, editor

Published
2013
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8. Robust and Accurate Shape Model Fitting Using Random Forest Regression Voting

Author

Cootes, Tim F., Ionita, Mircea C., Lindner, Claudia, Sauer, Patrick, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Fitzgibbon, Andrew, editor, Lazebnik, Svetlana, editor, Perona, Pietro, editor, Sato, Yoichi, editor, and Schmid, Cordelia, editor

Published
2012
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9. Deformable Object Modelling and Matching

Author

Cootes, Tim F., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Kimmel, Ron, editor, Klette, Reinhard, editor, and Sugimoto, Akihiro, editor

Published
2011
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10. Segmentation of Lumbar Vertebrae Using Part-Based Graphs and Active Appearance Models

Author

Roberts, Martin G., Cootes, Tim F., Pacheco, Elisa, Oh, Teik, Adams, Judith E., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Yang, Guang-Zhong, editor, Hawkes, David, editor, Rueckert, Daniel, editor, Noble, Alison, editor, and Taylor, Chris, editor

Published
2009
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11. 3D Brain Segmentation Using Active Appearance Models and Local Regressors

Author

Babalola, Kolawole O., Cootes, Tim F., Twining, Carole J., Petrovic, Vlad, Taylor, Chris, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Metaxas, Dimitris, editor, Axel, Leon, editor, Fichtinger, Gabor, editor, and Székely, Gábor, editor

Published
2008
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12. Comparison and Evaluation of Segmentation Techniques for Subcortical Structures in Brain MRI

Author

Babalola, Kolawole O., Patenaude, Brian, Aljabar, Paul, Schnabel, Julia, Kennedy, David, Crum, William, Smith, Stephen, Cootes, Tim F., Jenkinson, Mark, Rueckert, Daniel, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Metaxas, Dimitris, editor, Axel, Leon, editor, Fichtinger, Gabor, editor, and Székely, Gábor, editor

Published
2008
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22. Predicting the mechanical hip–knee–ankle angle accurately from standard knee radiographs: a cross-validation experiment in 100 patients

Author

Gielis, Willem Paul (author), Rayegan, Hassan (author), Arbabi, V. (author), Ahmadi Brooghani, Seyed Y. (author), Lindner, Claudia (author), Cootes, Tim F. (author), de Jong, Pim A. (author), Weinans, H.H. (author), Custers, Roel J.H. (author), Gielis, Willem Paul (author), Rayegan, Hassan (author), Arbabi, V. (author), Ahmadi Brooghani, Seyed Y. (author), Lindner, Claudia (author), Cootes, Tim F. (author), de Jong, Pim A. (author), Weinans, H.H. (author), and Custers, Roel J.H. (author)

Abstract

Background and purpose — Being able to predict the hip–knee–ankle angle (HKAA) from standard knee radiographs allows studies on malalignment in cohorts lacking full-limb radiography. We aimed to develop an automated image analysis pipeline to measure the femoro-tibial angle (FTA) from standard knee radiographs and test various FTA definitions to predict the HKAA. Patients and methods — We included 110 pairs of standard knee and full-limb radiographs. Automatic search algorithms found anatomic landmarks on standard knee radiographs. Based on these landmarks, the FTA was automatically calculated according to 9 different definitions (6 described in the literature and 3 newly developed). Pearson and intra-class correlation coefficient [ICC]) were determined between the FTA and HKAA as measured on full-limb radiographs. Subsequently, the top 4 FTA definitions were used to predict the HKAA in a 5-fold cross-validation setting. Results — Across all pairs of images, the Pearson correlations between FTA and HKAA ranged between 0.83 and 0.90. The ICC values from 0.83 to 0.90. In the cross-validation experiments to predict the HKAA, these values decreased only minimally. The mean absolute error for the best method to predict the HKAA from standard knee radiographs was 1.8° (SD 1.3). Interpretation — We showed that the HKAA can be automatically predicted from standard knee radiographs with fair accuracy and high correlation compared with the true HKAA. Therefore, this method enables research of the relationship between malalignment and knee pathology in large (epidemiological) studies lacking full-limb radiography., Biomaterials & Tissue Biomechanics

Published
2020
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23. Predicting the mechanical hip–knee–ankle angle accurately from standard knee radiographs: a cross-validation experiment in 100 patients

Author

ORT Research, Other research (not in main researchprogram), Orthopaedie Onderzoek, Researchgr. Systems Radiology, Circulatory Health, Infection & Immunity, Regenerative Medicine and Stem Cells, Cancer, MS Orthopaedie Algemeen, Gielis, Willem Paul, Rayegan, Hassan, Arbabi, Vahid, Ahmadi Brooghani, Seyed Y., Lindner, Claudia, Cootes, Tim F., de Jong, Pim A., Weinans, H., Custers, Roel J.H., ORT Research, Other research (not in main researchprogram), Orthopaedie Onderzoek, Researchgr. Systems Radiology, Circulatory Health, Infection & Immunity, Regenerative Medicine and Stem Cells, Cancer, MS Orthopaedie Algemeen, Gielis, Willem Paul, Rayegan, Hassan, Arbabi, Vahid, Ahmadi Brooghani, Seyed Y., Lindner, Claudia, Cootes, Tim F., de Jong, Pim A., Weinans, H., and Custers, Roel J.H.

Published
2020

27. A minimum description length approach to statistical shape modeling

Author

Davies, Rhodri H., Twining, Carole J., Cootes, Tim F., Waterton, John C., and Taylor, Chris. J.

Subjects
Diagnostic imaging -- Analysis, Image processing -- Methods, Business, Electronics, Electronics and electrical industries, Health care industry
Abstract

We describe a method for automatically building statistical shape models from a training set of example boundaries/surfaces. These models show considerable promise as a basis for segmenting and interpreting images. One of the drawbacks of the approach is, however, the need to establish a set of dense correspondences between all members of a set of training shapes. Often this is achieved by locating a set of 'landmarks' manually on each training image, which is time consuming and subjective in two dimensions and almost impossible in three dimensions. We describe how shape models can be built automatically by posing the correspondence problem as one of finding the parameterization for each shape in the training set. We select the set of parameterizations that build the 'best' model. We define 'best' as that which minimizes the description length of the training set, arguing that this leads to models with good compactness, specificity and generalization ability. We show how a set of shape parameterizations can be represented and manipulated in order to build a minimum description length model. Results are given for several different training sets of two-dimensional boundaries, showing that the proposed method constructs better models than other approaches including manual landmarking--the current gold standard. We also show that the method can be extended straightforwardly to three dimensions. Index Terms--Active shape models, automatic landmarking, correspondence problem, minimum description length (MDL), point distribution models, statistical shape modeling.

Published
2002

47. Integrated presentation of 3-D data derived from multisensor imagery and anatomical atlases using a parallel processing system

Author

Undrill, Peter E., primary, Cameron, George G., additional, Cookson, M. J., additional, Davies, Chris, additional, Robinson, Neil L., additional, Hill, Andrew, additional, Cootes, Tim F., additional, Taylor, Christopher J., additional, Thornham, Ann, additional, Wysocki, J., additional, Liddell, Heather M., additional, and Parkinson, Dennis J., additional

Published
1992
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