Kenji Suzuki
Titolo
Citata da
Citata da
Anno
Linear-time connected-component labeling based on sequential local operations
K Suzuki, I Horiba, N Sugie
Computer Vision and Image Understanding 89 (1), 1-23, 2003
5662003
Fast connected-component labeling
L He, Y Chao, K Suzuki, K Wu
Pattern recognition 42 (9), 1977-1987, 2009
3382009
Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low‐dose computed tomography
K Suzuki, SG Armato III, F Li, S Sone, K Doi
Medical physics 30 (7), 1602-1617, 2003
3002003
A run-based two-scan labeling algorithm
L He, Y Chao, K Suzuki
IEEE transactions on image processing 17 (5), 749-756, 2008
2772008
Optimizing two-pass connected-component labeling algorithms
K Wu, E Otoo, K Suzuki
Pattern Analysis and Applications 12 (2), 117-135, 2009
2482009
Computer-aided diagnostic scheme for distinction between benign and malignant nodules in thoracic low-dose CT by use of massive training artificial neural network
K Suzuki, F Li, S Sone, K Doi
IEEE transactions on medical imaging 24 (9), 1138-1150, 2005
2362005
Prognostic value of metabolic tumor burden on 18F-FDG PET in nonsurgical patients with non-small cell lung cancer
S Liao, BC Penney, K Wroblewski, H Zhang, CA Simon, R Kampalath, ...
European journal of nuclear medicine and molecular imaging 39 (1), 27-38, 2012
2302012
Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN)
K Suzuki, H Abe, H MacMahon, K Doi
IEEE Transactions on medical imaging 25 (4), 406-416, 2006
2172006
Computer-Aided Diagnosis Systems for Lung Cancer: Challenges and Methodologies
A El-Baz, GM Beache, G Gimel'farb, K Suzuki, K Okada, A Elnakib, ...
International Journal of Biomedical Imaging 2013, 2013
2132013
Computerized scheme for automated detection of lung nodules in low-dose computed tomography images for lung cancer screening1
H Arimura, S Katsuragawa, K Suzuki, F Li, J Shiraishi, S Sone, K Doi
Academic radiology 11 (6), 617-629, 2004
2022004
Overview of deep learning in medical imaging
K Suzuki
Radiological physics and technology 10 (3), 257-273, 2017
2002017
Quantitative computerized analysis of diffuse lung disease in high‐resolution computed tomography
Y Uchiyama, S Katsuragawa, H Abe, J Shiraishi, F Li, Q Li, CT Zhang, ...
Medical Physics 30 (9), 2440-2454, 2003
1902003
Neural edge enhancer for supervised edge enhancement from noisy images
K Suzuki, I Horiba, N Sugie
IEEE Transactions on Pattern Analysis and Machine Intelligence 25 (12), 1582…, 2003
1702003
False-positive reduction in computer-aided diagnostic scheme for detecting nodules in chest radiographs by means of massive training artificial neural network1
K Suzuki, J Shiraishi, H Abe, H MacMahon, K Doi
Academic radiology 12 (2), 191-201, 2005
1612005
Artificial Neural Networks - Methodological Advances and Biomedical Applications
K Suzuki
InTech, 2011
1412011
A dual‐stage method for lesion segmentation on digital mammograms
Y Yuan, ML Giger, H Li, K Suzuki, C Sennett
Medical physics 34 (11), 4180-4193, 2007
1312007
Image modification and detection using massive training artificial neural networks (MTANN)
K Suzuki, K Doi
US Patent 7,545,965, 2009
1232009
Computer-aided Detection of Peripheral Lung Cancers Missed at CT: ROC Analyses without and with Localization1
F Li, H Arimura, K Suzuki, J Shiraishi, Q Li, H Abe, R Engelmann, S Sone, ...
Radiology 237 (2), 684, 2005
1172005
Radiologists' performance for differentiating benign from malignant lung nodules on high-resolution CT using computer-estimated likelihood of malignancy
F Li, M Aoyama, J Shiraishi, H Abe, Q Li, K Suzuki, R Engelmann, S Sone, ...
American Journal of Roentgenology 183 (5), 1209-1215, 2004
1172004
Proceedings of the Second international conference on Machine learning in medical imaging
K Suzuki, F Wang, D Shen, P Yan
Springer-Verlag, 2011
108*2011
Il sistema al momento non pu eseguire l'operazione. Riprova pi tardi.
Articoli 1–20