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News
Congratulation to Fu Li for getting his paper published in IEEE UFFC! The USCT breast phantom dataset is now publicly available on Harvard Dataverse.
Ultrasound computed tomography (USCT) is an emerging imaging modality for breast imaging that can produce quantitative images that depict the acoustic properties of tissues. Computer-simulation studies, also known as virtual imaging trials, provide researchers with an economical and convenient route to systematically explore imaging system designs and image reconstruction methods. When simulating an imaging technology […]
Congratulations to Xiaohui for getting her first neuroimaging paper published on Cerebral Cortex!
Our recent paper introduces a multivariate functional connectivity approach to mapping brain networks and imputing neural activity in mice. Paper Link: https://academic.oup.com/cercor/advance-article/doi/10.1093/cercor/bhab282/6372091?guestAccessKey=7e979214-771c-463e-8d2a-7907fdd5b0b2
Congrats to Kaiyan Li for getting his IEEE TMI paper on task-based analysis of denoising networks published!
The paper link is attached: https://ieeexplore.ieee.org/abstract/document/9419965
Congrats to Sayantan and Varun for getting their IEEE TMI paper on hallucinations published!
Our recent paper in IEEE TMI: Second Special Issue on Machine Learning for Image Reconstruction formally defines the notion of hallucinations due to regularized reconstruction methods in tomographic imaging. Paper: https://arxiv.org/abs/2012.00646 Code: https://github.com/comp-imaging-sci/hallucinations-tomo-recon
PhD student Varun Kelkar presented in ICML 2021 on “Prior Image-Constrained Reconstruction using Style-Based Generative Models”.
Our new #ICML2021 paper talks about a new formulation of a classical problem, where a “prior image” is used to help solve highly ill-posed imaging inverse problems. Basically, we use StyleGANs and the style-separation it provides to measure the difference between the sought-after and the prior image, and then formulate a constrained optimization problem in […]