My internal journal
With President Ronald J. Daniels on the Commencement of Johns Hopkins University
May 24th, 2015
With my advisor Dr. Miller
Jan 6th, 2015
(The last day working at [email protected])
I passed my PhD thesis defense. Now I am Dr. Feng! :D
I start working at Google. Now I am a Googler! :D
I am a PhD candidate working with Dr. Michael I. Miller, in the Center for Imaging Science (CIS) at Dept. of Electrical and Computer Engineering, Johns Hopkins University.
- Medical image analysis:
- MR image segmentation
- cortical thickness measurement.
- Machine learning:
- Computer aided diagnosis
- application of feature extraction/selection, data fusion, dictionary learning, and deep learning.
- Natural Image processing/analysis/retrieval:
- Content-based image retrieval (CBIR)
- Face detection/recognition.
Note: For details of these projects listed here as well as my industry projects, please refer to the Projects page.
- Machine Learning in Computational Anatomy (3D MR images). 09/2013 -
- Extract shape and appearance features from MR brain images.
- Super-high-dimension classification between disease of Alzheimer's type and normal aging cases.
- Explored deep learning, sparse coding and manifold learning applied to medical images.
- Shape Analysis for Alzheimer's Disease.
- Surface-based shape feature extraction via manifold learning method.
- Classification between Alzheimer's disease and healthy control group.
- 3-D image registration (MR image of full-body)
- Developed a pipeline for full-body MRI registration by applying multi-channel Large Deformation Diffeomorphic Metric Mapping (McLDDMM).
- Brain MRI image analysis, Gray matter thickness measurement.
- Created a pipeline for measuring gray matter thickness from MR images.
- Face Recognition Project
- Implemented a prototype system of face-recognition. Occlusion and shadow are removed by Robust Principle Component Analysis.
- Compared the performance of sparse representation classifier and SVM on Feret database.
- Content-based Image Retrieval (CBIR) project. 09/2007 - 07/2008
- Implemented a web-based prototype of CBIR, running on a 10,000-image database.
- Developed a new Query-by-Multiple-Example method based on user's feedback to refine the result.
- Jianqiao Feng, Minh Tang, Michael Miller, Multiple structure analysis for Alzheimer's disease, 2014 (in processing)
- Jianqiao Feng, X Tang, M Tang, C Priebe, M Miller, Metric Space Structures for Computational Anatomy, Machine Learning in Medical Imaging, 123-130
- Jianqiao Feng, Pingli Li, Wenhua Jia, Xiangyu Qiu, Mengyou Yuan, A new edge enhancement on halftone image, Electric Information and Control Engineering (ICEICE), 2011.
- Jianqiao Feng, Haifeng Zhao, Wenhua Jia, A New Adaptive Distance Computation Technique for Query-by-Multiple-Example System, in proceedings of IEEE International conference on Signal-Image Technology & Internet-Based Systems(SITIS' 08), 2008.
- Segars, W. P., Jason Bond, Jack Frush, Sylvia Hon, Chris Eckersley, Cameron H. Williams, Jianqiao Feng et al. "Population of anatomically variable 4D XCAT adult phantoms for imaging research and optimization." Medical physics 40, no. 4 (2013): 043701.
- Cai, Zhuhua, Ruichuan Chen, Jianqiao Feng, Cong Tang, Zhong Chen, and Jianbin Hu. "A holistic mechanism against file pollution in peer-to-peer networks." In Proceedings of the 2009 ACM symposium on Applied Computing, pp. 28-34. ACM, 2009.
- Bond, Jason, Jack Frush, Sylvia Hon, Chris Eckersley, Cameron H. Williams, Jianqiao Feng, Daniel J. Tward et al. "Series of 4D adult XCAT phantoms for imaging research and dosimetry." In SPIE Medical Imaging, pp. 83130P-83130P. International Society for Optics and Photonics, 2012.
- US patent: Yu Zheng, Jianqiao Feng, Xing Xie, Weiying Ma, Detecting Spatial Outliers In A Location Entity Dataset, No. US20100179759.
- Chinese patent: Pingli Li, Jianqiao Feng, Novel Algorithm of Corner Detection on Halftone Image, 200810239368.8/CN101750883A.
Written with StackEdit. Last update: 07/07/2015 by Jianqiao Feng