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ORCIDNima Tajbakhsh
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2020 – today
- 2024
[i16]Rohit Jena, Ali Taghibakhshi, Sahil Jain, Gerald Shen, Nima Tajbakhsh, Arash Vahdat:
Elucidating Optimal Reward-Diversity Tradeoffs in Text-to-Image Diffusion Models. CoRR abs/2409.06493 (2024)- 2023
- [c25]Weinan Song, Gaurav Fotedar, Nima Tajbakhsh, Ziheng Zhou, Lei He, Xiaowei Ding:
MDT-Net: Multi-Domain Transfer by Perceptual Supervision for Unpaired Images in OCT Scan. ISBI 2023: 1-5 - [i15]Shengzhi Li, Nima Tajbakhsh:
SciGraphQA: A Large-Scale Synthetic Multi-Turn Question-Answering Dataset for Scientific Graphs. CoRR abs/2308.03349 (2023) - 2022
- [i14]Weinan Song, Gaurav Fotedar, Nima Tajbakhsh, Ziheng Zhou, Xiaowei Ding:
MDT-Net: Multi-domain Transfer by Perceptual Supervision for Unpaired Images in OCT Scan. CoRR abs/2203.06363 (2022) - 2021
- [j10]Nima Tajbakhsh, Holger Roth, Demetri Terzopoulos, Jianming Liang
:
Guest Editorial Annotation-Efficient Deep Learning: The Holy Grail of Medical Imaging. IEEE Trans. Medical Imaging 40(10): 2526-2533 (2021) - [c24]Qinji Yu, Kang Dang, Nima Tajbakhsh, Demetri Terzopoulos, Xiaowei Ding:
A Location-Sensitive Local Prototype Network For Few-Shot Medical Image Segmentation. ISBI 2021: 262-266 - [i13]Qinji Yu, Kang Dang, Nima Tajbakhsh, Demetri Terzopoulos, Xiaowei Ding:
A Location-Sensitive Local Prototype Network for Few-Shot Medical Image Segmentation. CoRR abs/2103.10178 (2021) - 2020
- [j9]Abdullah-Al-Zubaer Imran, Ali Hatamizadeh, Shilpa P. Ananth, Xiaowei Ding, Nima Tajbakhsh, Demetri Terzopoulos:
Fast and automatic segmentation of pulmonary lobes from chest CT using a progressive dense V-network. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 8(5): 509-518 (2020) - [j8]Nima Tajbakhsh, Laura Jeyaseelan, Qian Li, Jeffrey N. Chiang, Zhihao Wu, Xiaowei Ding:
Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation. Medical Image Anal. 63: 101693 (2020) - [j7]Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, Jianming Liang:
UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation. IEEE Trans. Medical Imaging 39(6): 1856-1867 (2020) - [c23]Nima Tajbakhsh, Brian Lai, Shilpa P. Ananth, Xiaowei Ding:
ErrorNet: Learning Error Representations from Limited Data to Improve Vascular Segmentation. ISBI 2020: 1364-1368 - [c22]Gaurav Fotedar, Nima Tajbakhsh, Shilpa P. Ananth, Xiaowei Ding:
Extreme Consistency: Overcoming Annotation Scarcity and Domain Shifts. MICCAI (1) 2020: 699-709 - [i12]Germán González, Daniel Jimenez-Carretero, Sara Rodríguez-López, Carlos Cano-Espinosa, Miguel Cazorla, Tanya Agarwal, Vinit Agarwal, Nima Tajbakhsh, Michael B. Gotway, Jianming Liang, Mojtaba Masoudi, Noushin Eftekhari, Mahdi Saadatmand Tarzjan, Hamid-Reza Pourreza, Patricia Fraga-Rivas, Eduardo Fraile Moreno, Frank J. Rybicki, Ara Kassarjian, Raúl San José Estépar, María J. Ledesma-Carbayo:
Computer Aided Detection for Pulmonary Embolism Challenge (CAD-PE). CoRR abs/2003.13440 (2020) - [i11]Gaurav Fotedar, Nima Tajbakhsh, Shilpa P. Ananth, Xiaowei Ding:
Extreme Consistency: Overcoming Annotation Scarcity and Domain Shifts. CoRR abs/2004.11966 (2020)
2010 – 2019
- 2019
- [j6]Nima Tajbakhsh, Jae Y. Shin, Michael B. Gotway, Jianming Liang:
Computer-aided detection and visualization of pulmonary embolism using a novel, compact, and discriminative image representation. Medical Image Anal. 58 (2019) - [c21]Md Mahfuzur Rahman Siddiquee, Zongwei Zhou, Nima Tajbakhsh, Ruibin Feng, Michael B. Gotway, Yoshua Bengio, Jianming Liang:
Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization. ICCV 2019: 191-200 - [c20]Nima Tajbakhsh, Yufei Hu, Junli Cao, Xingjian Yan, Yi Xiao, Yong Lu, Jianming Liang, Demetri Terzopoulos, Xiaowei Ding:
Surrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data. ISBI 2019: 1251-1255 - [c19]Zongwei Zhou, Vatsal Sodha, Md Mahfuzur Rahman Siddiquee, Ruibin Feng, Nima Tajbakhsh, Michael B. Gotway, Jianming Liang:
Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis. MICCAI (4) 2019: 384-393 - [i10]Nima Tajbakhsh, Yufei Hu, Junli Cao, Xingjian Yan, Yi Xiao, Yong Lu, Jianming Liang, Demetri Terzopoulos, Xiaowei Ding:
Surrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data. CoRR abs/1901.08707 (2019) - [i9]Abdullah-Al-Zubaer Imran, Ali Hatamizadeh, Shilpa P. Ananth, Xiaowei Ding, Demetri Terzopoulos, Nima Tajbakhsh:
Automatic Segmentation of Pulmonary Lobes Using a Progressive Dense V-Network. CoRR abs/1902.06362 (2019) - [i8]Zongwei Zhou, Vatsal Sodha, Md Mahfuzur Rahman Siddiquee, Ruibin Feng, Nima Tajbakhsh, Michael B. Gotway, Jianming Liang:
Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis. CoRR abs/1908.06912 (2019) - [i7]Md Mahfuzur Rahman Siddiquee, Zongwei Zhou, Nima Tajbakhsh, Ruibin Feng, Michael B. Gotway, Yoshua Bengio, Jianming Liang:
Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization. CoRR abs/1908.06965 (2019) - [i6]Nima Tajbakhsh, Laura Jeyaseelan, Qian Li, Jeffrey N. Chiang, Zhihao Wu, Xiaowei Ding:
Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation. CoRR abs/1908.10454 (2019) - [i5]Nima Tajbakhsh, Brian Lai, Shilpa P. Ananth, Xiaowei Ding:
ErrorNet: Learning error representations from limited data to improve vascular segmentation. CoRR abs/1910.04814 (2019) - [i4]Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, Jianming Liang:
UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation. CoRR abs/1912.05074 (2019) - 2018
- [c18]Nazanin Makkinejad, Nima Tajbakhsh, Amin Zarshenas, Ashfaq Khokhar, Kenji Suzuki:
Reduction in training time of a deep learning model in detection of lesions in CT. Medical Imaging: Computer-Aided Diagnosis 2018: 105753V - [c17]Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, Jianming Liang:
UNet++: A Nested U-Net Architecture for Medical Image Segmentation. DLMIA/ML-CDS@MICCAI 2018: 3-11 - [c16]Abdullah-Al-Zubaer Imran, Ali Hatamizadeh, Shilpa P. Ananth, Xiaowei Ding, Demetri Terzopoulos, Nima Tajbakhsh:
Automatic Segmentation of Pulmonary Lobes Using a Progressive Dense V-Network. DLMIA/ML-CDS@MICCAI 2018: 282-290 - [i3]Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, Jianming Liang:
UNet++: A Nested U-Net Architecture for Medical Image Segmentation. CoRR abs/1807.10165 (2018) - 2017
- [j5]Nima Tajbakhsh, Kenji Suzuki:
Comparing two classes of end-to-end machine-learning models in lung nodule detection and classification: MTANNs vs. CNNs. Pattern Recognit. 63: 476-486 (2017) - [c15]Zijie Yuan, Mohammadhassan Izadyyazdanabadi, Divya Mokkapati, Rujuta Panvalkar, Jae Y. Shin, Nima Tajbakhsh, Suryakanth R. Gurudu, Jianming Liang:
Automatic polyp detection in colonoscopy videos. Medical Imaging: Image Processing 2017: 101332K - [p2]Nima Tajbakhsh, Jae Y. Shin, R. Todd Hurst, Christopher B. Kendall, Jianming Liang:
Automatic Interpretation of Carotid Intima-Media Thickness Videos Using Convolutional Neural Networks. Deep Learning for Medical Image Analysis 2017: 105-131 - [p1]Nima Tajbakhsh, Jae Y. Shin, Suryakanth R. Gurudu, R. Todd Hurst, Christopher B. Kendall, Michael B. Gotway, Jianming Liang:
On the Necessity of Fine-Tuned Convolutional Neural Networks for Medical Imaging. Deep Learning and Convolutional Neural Networks for Medical Image Computing 2017: 181-193 - [i2]Nima Tajbakhsh, Jae Y. Shin, Suryakanth R. Gurudu, R. Todd Hurst, Christopher B. Kendall, Michael B. Gotway, Jianming Liang:
Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning? CoRR abs/1706.00712 (2017) - [i1]Jae Y. Shin, Nima Tajbakhsh, R. Todd Hurst, Christopher B. Kendall, Jianming Liang:
Automating Carotid Intima-Media Thickness Video Interpretation with Convolutional Neural Networks. CoRR abs/1706.00719 (2017) - 2016
- [j4]Nima Tajbakhsh, Suryakanth R. Gurudu, Jianming Liang:
Automated Polyp Detection in Colonoscopy Videos Using Shape and Context Information. IEEE Trans. Medical Imaging 35(2): 630-644 (2016) - [j3]Nima Tajbakhsh, Jae Y. Shin, Suryakanth R. Gurudu, R. Todd Hurst, Christopher B. Kendall, Michael B. Gotway, Jianming Liang:
Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning? IEEE Trans. Medical Imaging 35(5): 1299-1312 (2016) - [c14]Jae Y. Shin, Nima Tajbakhsh, R. Todd Hurst, Christopher B. Kendall, Jianming Liang:
Automating Carotid Intima-Media Thickness Video Interpretation with Convolutional Neural Networks. CVPR 2016: 2526-2535 - 2015
- [b1]Nima Tajbakhsh:
Ensuring High-Quality Colonoscopy by Reducing Polyp Miss-Rates. Arizona State University, Tempe, USA, 2015 - [c13]Nima Tajbakhsh, Suryakanth R. Gurudu, Jianming Liang:
A Comprehensive Computer-Aided Polyp Detection System for Colonoscopy Videos. IPMI 2015: 327-338 - [c12]Nima Tajbakhsh, Suryakanth R. Gurudu, Jianming Liang:
Automatic polyp detection in colonoscopy videos using an ensemble of convolutional neural networks. ISBI 2015: 79-83 - [c11]Nima Tajbakhsh, Michael B. Gotway, Jianming Liang:
Computer-Aided Pulmonary Embolism Detection Using a Novel Vessel-Aligned Multi-planar Image Representation and Convolutional Neural Networks. MICCAI (2) 2015: 62-69 - 2014
- [c10]Nima Tajbakhsh, Changching Chi, Suryakanth R. Gurudu, Jianming Liang:
Automatic polyp detection from learned boundaries. ISBI 2014: 97-100 - [c9]Nima Tajbakhsh, Changching Chi, Haripriya Sharma, Qing Wu, Suryakanth R. Gurudu, Jianming Liang:
Automatic Assessment of Image Informativeness in Colonoscopy. ABDI@MICCAI 2014: 151-158 - [c8]Nima Tajbakhsh, Suryakanth R. Gurudu, Jianming Liang:
Automatic Polyp Detection Using Global Geometric Constraints and Local Intensity Variation Patterns. MICCAI (2) 2014: 179-187 - 2013
- [j2]Nima Tajbakhsh, Hong Wu, Wenzhe Xue, Michael B. Gotway, Jianming Liang:
A novel online boosting algorithm for automatic anatomy detection. Mach. Vis. Appl. 24(7): 1359-1370 (2013) - [c7]Nima Tajbakhsh, Suryakanth R. Gurudu, Jianming Liang:
A Classification-Enhanced Vote Accumulation Scheme for Detecting Colonic Polyps. Abdominal Imaging 2013: 53-62 - 2012
- [c6]Hong Wu, Nima Tajbakhsh, Wenzhe Xue, Jianming Liang:
Self-adaptive asymmetric on-line boosting for detecting anatomical structures. Medical Imaging: Computer-Aided Diagnosis 2012: 831539 - 2011
- [c5]Nima Tajbakhsh, Hong Wu, Wenzhe Xue, Jianming Liang:
Automated Detection of Major Thoracic Structures with a Novel Online Learning Method. MLMI 2011: 273-281 - 2010
- [j1]Nima Tajbakhsh, Babak Nadjar Araabi, Hamid Soltanian-Zadeh:
Robust Iris Verification Based on Local and Global Variations. EURASIP J. Adv. Signal Process. 2010 (2010)
2000 – 2009
- 2009
- [c4]Nima Tajbakhsh, Khashayar Misaghian, Naghmeh Mohammadi Bandari:
A Region-Based Iris Feature Extraction Method Based on 2D-Wavelet Transform. COST 2101/2102 Conference 2009: 301-307 - [c3]Nima Tajbakhsh, Babak Nadjar Araabi, Hamid Soltanian-Zadeh:
Noisy Iris Verification: A Modified Version of Local Intensity Variation Method. ICB 2009: 1150-1159 - 2008
- [c2]Nima Tajbakhsh, Babak Nadjar Araabi, Hamid Soltanian-Zadeh:
Feature fusion as a practical solution toward noncooperative iris recognition. FUSION 2008: 1-7 - [c1]Nima Tajbakhsh, Babak Nadjar Araabi, Hamid Soltanian-Zadeh:
An intelligent decision combiner applied to noncooperative iris recognition. FUSION 2008: 1-6
Coauthor Index
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