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ORCIDAmir Hossein Foruzan
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2020 – today
- 2024
[j27]Mina Esfandiarkhani, Amir Hossein Foruzan:
Impact of a generalised SVG-based large-scale super-resolution algorithm on the design of light-weight medical image segmentation DNNs. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 11(7) (2024)- [j26]Mina Esfandiarkhani, Amir Hossein Foruzan
, Yen-Wei Chen:
A Study on the Validity and Scope of Self-Similarity Property in Super-Resolution of Medical Images. Circuits Syst. Signal Process. 43(7): 4298-4318 (2024) - 2023
- [j25]Saeed Moslehi, Amir Hossein Foruzan, Yen-Wei Chen, Hongjie Hu:
Characterisation of focal liver lesions in multi-phase CT images using textural and pathological descriptors. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 11(4): 1523-1531 (2023) - 2022
- [j24]Saeed Mohagheghi, Amir Hossein Foruzan:
Developing an explainable deep learning boundary correction method by incorporating cascaded x-Dim models to improve segmentation defects in liver CT images. Comput. Biol. Medicine 140: 105106 (2022) - [j23]Hamid Moradi, Amir Hossein Foruzan:
Integration of Dynamic Multi-Atlas and Deep Learning Techniques to Improve Segmentation of the Prostate in MR Images. Int. J. Image Graph. 22(4): 2250031:1-2250031:17 (2022) - 2021
- [j22]Mahdieh Akbari, Amir Hossein Foruzan, Yen-Wei Chen, Hongjie Hu:
Reducing reconstruction error of classified textural patches by integration of random forests and coupled dictionary nonlinear regressors: with applications to super-resolution of abdominal CT images. Int. J. Comput. Assist. Radiol. Surg. 16(9): 1469-1480 (2021) - [j21]Sepide Farhang, Amir Hossein Foruzan:
A low-complexity volumetric model with dynamic inter-connections to represent human liver in surgical simulators. Int. J. Medical Eng. Informatics 13(2): 121-128 (2021) - [j20]Saeed Mohagheghi, Mehdi Alizadeh, Seyed Mahdi Safavi, Amir Hossein Foruzan, Yen-Wei Chen:
Integration of CNN, CBMIR, and Visualization Techniques for Diagnosis and Quantification of Covid-19 Disease. IEEE J. Biomed. Health Informatics 25(6): 1873-1880 (2021) - 2020
- [j19]Nasim Nasiri, Amir Hossein Foruzan, Yen-Wei Chen:
Integration of a knowledge-based constraint into generative models with applications in semi-automatic segmentation of liver tumors. Biomed. Signal Process. Control. 57 (2020) - [j18]Saeed Mohagheghi, Amir Hossein Foruzan:
Incorporating prior shape knowledge via data-driven loss model to improve 3D liver segmentation in deep CNNs. Int. J. Comput. Assist. Radiol. Surg. 15(2): 249-257 (2020)
2010 – 2019
- 2019
- [j17]Ali Derakhshani, Amir Hossein Foruzan:
Predicting the principal strong ground motion parameters: A deep learning approach. Appl. Soft Comput. 80: 192-201 (2019) - [j16]Mahdi Delavari, Amir Hossein Foruzan, Yen-Wei Chen:
Accurate point correspondences using a modified coherent point drift algorithm. Biomed. Signal Process. Control. 52: 429-444 (2019) - [j15]Titinunt Kitrungrotsakul, Xian-Hua Han, Yutaro Iwamoto, Lanfen Lin, Amir Hossein Foruzan, Wei Xiong, Yen-Wei Chen:
VesselNet: A deep convolutional neural network with multi pathways for robust hepatic vessel segmentation. Comput. Medical Imaging Graph. 75: 74-83 (2019) - [j14]Mansoureh Sadat Mirasadi, Amir Hossein Foruzan:
Content-based medical image retrieval of CT images of liver lesions using manifold learning. Int. J. Multim. Inf. Retr. 8(4): 233-240 (2019) - [j13]Atefe Hassani, Amir Hossein Foruzan:
Improved PPG-based estimation of the blood pressure using latent space features. Signal Image Video Process. 13(6): 1141-1147 (2019) - 2018
- [j12]Neda Sangsefidi, Amir Hossein Foruzan, Ardeshir Dolati:
Balancing the data term of graph-cuts algorithm to improve segmentation of hepatic vascular structures. Comput. Biol. Medicine 93: 117-126 (2018) - [j11]Mahdi Delavari, Amir Hossein Foruzan:
Anatomical decomposition of human liver volume to build accurate statistical shape models. Signal Image Video Process. 12(2): 331-338 (2018) - 2017
- [j10]Mina Esfandiarkhani, Amir Hossein Foruzan:
A generalized active shape model for segmentation of liver in low-contrast CT volumes. Comput. Biol. Medicine 82: 59-70 (2017) - [c10]Neda Sangsefidi, Amir Hossein Foruzan, Ardeshir Dolati, Yen-Wei Chen:
Incorporating a locally estimated appearance model in the graphcuts algorithm to extract small hepatic vessels. ICIP 2017: 2324-2328 - [c9]Titinunt Kitrungrotsakul, Xian-Hua Han, Yutaro Iwamoto, Amir Hossein Foruzan, Lanfen Lin, Yen-Wei Chen:
Robust hepatic vessel segmentation using multi deep convolution network. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2017: 1013711 - 2016
- [j9]Amir Hossein Foruzan, Yen-Wei Chen:
Improved segmentation of low-contrast lesions using sigmoid edge model. Int. J. Comput. Assist. Radiol. Surg. 11(7): 1267-1283 (2016) - [c8]Chunhua Dong, Yen-Wei Chen, Amir Hossein Foruzan, Xian-Hua Han, Tomoko Tateyama, Xing Wu:
A framework for probabilistic atlas-based organ segmentation. Medical Imaging: Image Processing 2016: 97842X - 2015
- [j8]Amir Hossein Foruzan, Hossein Rajabzadeh Motlagh:
Multimodality liver registration of Open-MR and CT scans. Int. J. Comput. Assist. Radiol. Surg. 10(8): 1253-1267 (2015) - [j7]Chunhua Dong, Yen-Wei Chen, Amir Hossein Foruzan, Lanfen Lin, Xian-Hua Han, Tomoko Tateyama, Xing Wu, Gang Xu, Huiyan Jiang:
Segmentation of liver and spleen based on computational anatomy models. Comput. Biol. Medicine 67: 146-160 (2015) - 2014
- [j6]Amir Hossein Foruzan, Yen-Wei Chen, Masatoshi Hori, Yoshinobu Sato, Noriyuki Tomiyama:
Capturing large shape variations of liver using population-based statistical shape models. Int. J. Comput. Assist. Radiol. Surg. 9(6): 967-977 (2014) - [c7]Yen-Wei Chen, Amir Hossein Foruzan, Chunhua Dong, Tomoko Tateyama, Xianhua Han:
Automatic Segmentation of Liver From CT Images Using Probabilistic Atlas and Template Matching. IDT/IIMSS/STET 2014: 412-420 - 2013
- [j5]Amir Hossein Foruzan, Iman Kalantari Khandani, Shahriar Baradaran Shokouhi:
Segmentation of brain tissues using a 3-D multi-layer Hidden Markov Model. Comput. Biol. Medicine 43(2): 121-130 (2013) - [j4]Amir Hossein Foruzan, Yen-Wei Chen, Reza Aghaeizadeh Zoroofi, Akira Furukawa, Yoshinobu Sato, Masatoshi Hori, Noriyuki Tomiyama:
Segmentation of Liver in Low-Contrast Images Using K-Means Clustering and Geodesic Active Contour Algorithms. IEICE Trans. Inf. Syst. 96-D(4): 798-807 (2013) - [c6]Yen-Wei Chen, Masaki Kaibori, Tsukasa Shindo, Kousuke Miyawaki, Amir Hossein Foruzan, Tomoko Tateyama, Xian-Hua Han, Kosuke Matsui, Takumi Tsuda, A.-Hon Kwon:
Computer-aided liver surgical planning system using CT volumes. EMBC 2013: 2360-2363 - 2012
- [j3]Amir Hossein Foruzan, Reza Aghaeizadeh Zoroofi, Yoshinobu Sato, Masatoshi Hori:
A Hessian-based filter for vascular segmentation of noisy hepatic CT scans. Int. J. Comput. Assist. Radiol. Surg. 7(2): 199-205 (2012) - 2011
- [c5]Shinya Kohara, Tomoko Tateyama, Amir Hossein Foruzan, Akira Furukawa, Shuzo Kanasaki, Makoto Wakamiya, Xiong Wei, Yen-Wei Chen:
Preliminary study on statistical shape model applied to diagnosis of liver cirrhosis. ICIP 2011: 2921-2924 - 2010
- [c4]Yen-Wei Chen, Katsumi Tsubokawa, Amir Hossein Foruzan:
Liver Segmentation from Low Contrast Open MR Scans Using K-Means Clustering and Graph-Cuts. ISNN (2) 2010: 162-169
2000 – 2009
- 2009
- [j2]Amir Hossein Foruzan, Reza Aghaeizadeh Zoroofi, Masatoshi Hori, Yoshinobu Sato:
Liver segmentation by intensity analysis and anatomical information in multi-slice CT images. Int. J. Comput. Assist. Radiol. Surg. 4(3): 287-297 (2009) - [j1]Amir Hossein Foruzan, Reza Aghaeizadeh Zoroofi, Masatoshi Hori, Yoshinobu Sato:
A knowledge-based technique for liver segmentation in CT data. Comput. Medical Imaging Graph. 33(8): 567-587 (2009) - [c3]Tomoko Tateyama, Amir Hossein Foruzan, Yen-Wei Chen:
PCA Based Statical Shape Model of the Spleen. ICNC (6) 2009: 36-39 - [c2]Tomoko Tateyama, Amir Hossein Foruzan, Yen-Wei Chen:
2D-PCA Based Statistical Shape Model from few Medical Samples. IIH-MSP 2009: 1266-1269 - [c1]Amir Hossein Foruzan, Yen-Wei Chen, Reza Aghaeizadeh Zoroofi, Akira Furukawa, Yoshinobu Sato, Masatoshi Hori:
Multi-mode Narrow-band Thresholding with Application in Liver Segmentation from Low-contrast CT Images. IIH-MSP 2009: 1293-1296
Coauthor Index
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