Carlos Santiago
Carlos Santiago
Institute for Systems and Robotics (ISR/IST), LARSyS, Instituto Superior Técnico, Univ Lisboa
確認したメール アドレス: tecnico.ulisboa.pt - ホームページ
タイトル
引用先
引用先
2D Segmentation Using a Robust Active Shape Model With the EM Algorithm
C Santiago, J Nascimento, J Marques
Image Processing, IEEE Transactions on 24 (8), 2592-2601, 2015
252015
Fast segmentation of the left ventricle in cardiac MRI using dynamic programming
C Santiago, JC Nascimento, JS Marques
Computer methods and programs in biomedicine 154, 9-23, 2018
182018
A new ASM framework for left ventricle segmentation exploring slice variability in cardiac MRI volumes
C Santiago, JC Nascimento, JS Marques
Neural Computing and Applications 28 (9), 2489-2500, 2017
172017
Automatic 3-D segmentation of endocardial border of the left ventricle from ultrasound images
C Santiago, JC Nascimento, JS Marques
IEEE journal of biomedical and health informatics 19 (1), 339-348, 2014
152014
Segmentation of the left ventricle in cardiac MRI using a probabilistic data association active shape model
C Santiago, JC Nascimento, JS Marques
2015 37th Annual International Conference of the IEEE Engineering in …, 2015
112015
Fast and accurate segmentation of the LV in MR volumes using a deformable model with dynamic programming
C Santiago, JC Nascimento, JS Marques
2017 IEEE International Conference on Image Processing (ICIP), 1747-1751, 2017
62017
A robust active shape model using an expectation-maximization framework
C Santiago, JC Nascimento, JS Marques
2014 IEEE International Conference on Image Processing (ICIP), 6076-6080, 2014
62014
A new robust active shape model formulation for cardiac MRI segmentation
C Santiago, JC Nascimento, JS Marques
2016 IEEE International Conference on Image Processing (ICIP), 4112-4115, 2016
52016
Segmenting the left ventricle in cardiac in cardiac MRI: From handcrafted to deep region based descriptors
DO Medley, C Santiago, JC Nascimento
2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019 …, 2019
42019
Robust 3D Active Shape Model for the Segmentation of the Left Ventricle in MRI
C Santiago, JC Nascimento, JS Marques
Iberian Conference on Pattern Recognition and Image Analysis, 283-290, 2015
42015
A robust deformable model for 3D segmentation of the left ventricle from ultrasound data
C Santiago, JS Marques, JC Nascimento
Mathematical methodologies in pattern recognition and machine learning, 163-178, 2013
42013
Combining an active shape and motion models for object segmentation in image sequences
C Santiago, JC Nascimento, JS Marques
2018 25th IEEE International Conference on Image Processing (ICIP), 3703-3707, 2018
32018
3D left ventricular segmentation in echocardiography using a probabilistic data association deformable model
C Santiago, JC Nascimento, JS Marques
Image Processing (ICIP), 2013 20th IEEE International Conference on, 606-610, 2013
32013
Deep Active Shape Model for Robust Object Fitting
DO Medley, C Santiago, JC Nascimento
IEEE Transactions on Image Processing 29, 2380-2394, 2019
22019
Video analysis based on human pose for unsupervised summarization and retrieval
C Santiago, DM Alves, BQ Ferreira, J Carvalho, A Messina, JP Costeira
2019 International Conference on Content-Based Multimedia Indexing (CBMI), 1-6, 2019
22019
Robust feature descriptors for object segmentation using active shape models
D Medley, C Santiago, JC Nascimento
International Conference on Advanced Concepts for Intelligent Vision Systems …, 2018
22018
Unsupervised vehicle counting via multiple camera domain adaptation
L Ciampi, C Santiago, JP Costeira, C Gennaro, G Amato
arXiv preprint arXiv:2004.09251, 2020
12020
Performance evaluation of point matching algorithms for left ventricle motion analysis in MRI
C Santiago, JC Nascimento, JS Marques
2013 35th Annual International Conference of the IEEE Engineering in …, 2013
12013
Introduction of Human-Centric AI Assistant to Aid Radiologists for Multimodal Breast Image Classification
FM Calisto, C Santiago, N Nunes, JC Nascimento
International Journal of Human-Computer Studies, 102607, 2021
2021
LOW: Training deep neural networks by learning optimal sample weights
C Santiago, C Barata, M Sasdelli, G Carneiro, JC Nascimento
Pattern Recognition 110, 107585, 2020
2020
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