CMI Lab@WMIC 2019: Ziping & Hae Sol present.

The CMI lab had an excellent presence at the WMIC 2019 meeting. Ziping and Hae Sol presented their work on combining physics and machine learning for segmenting nuclear-medicine images. Dr. Jha gave an invited talk at the meeting. Overall, a great conference!

CMI Lab @WMIC 2019: Dr. Jha gives invited talk

At the WMIC 2019 meeting, Dr. Jha gave an invited talk on methods for quantitative medical imaging at the Imaging Data Science Forum. The focus of the talk was on new and improved methods for quantitative nuclear-medicine imaging, especially given the emergence of machine learning-based tools.

More accomplishments of summer interns

Qiye Tan and Jinxin Liu, summer interns at our lab, presented the outstanding work they have conducted during their stay here at a seminar yesterday. Best wishes to these two students as they go ahead in their careers.

Accomplishments of summer interns

Bo Yang and Tanya Hao, summer interns at our lab, presented their research on developing computational imaging solutions for radiology at the SU Internship seminar.

Abstracts on ML-based segmentation techniques accepted @WMIC2019

Two abstracts based on our work on developing new maching-learning-based approaches to segment SPECT and PET images have been accepted to the World Molecular Imaging Congress (WMIC) 2019. These efforts were led by Ziping Liu and Hae Sol Moon, and were thanks in large part due to the collaboration with the physicians at WashU!

Honor from SNMMI

Dr. Jha has been selected as Ones to Watch: 30 early career researchers making a difference in 2019 by the Society of Nuclear Medicine and Molecular Imaging (SNMMI).

Ziping, PhD student, joins lab

Delighted to share that Ziping Liu, PhD student from the Department of Biomedical Engineering at Washington University, joined the lab. Ziping obtained his Bachelors from the Department of Biomedical Engineering at University of Rochester. His research interests are in Task-specific medical imaging, PET System Modeling, and Image Analysis. Welcome Ziping! 

Asheq, PhD student, joins lab

Excited to share that Md Ashequr Rahman, PhD student from the Image Science PhD program, has joined the Computational Medical Imaging Lab. Asheq obtained his Bachelors in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology, Bangladesh. Welcome Asheq!

Dr. Jha delivers keynote at Siteman Oncologic Imaging program

Dr. Abhinav Jha presented the keynote at the Siteman Cancer Center Oncologic Imaging Research Program Student Poster Session and Special lecture. His talk was titled  “Computational Medical Imaging for Precision Medicine” and discussed various computational-imaging, that included machine-learning and model-based methods, to improve precision medicine. Further, excited to share that Priyanshu Jain, a student member […]

NIBIB Trailblazer award on SPECT reconstruction

Our lab has been awarded the NIBIB Trailblazer award for a project on developing new methods for transmission-less attenuation compensation in SPECT imaging! In this project, we propose to design and validate novel methods for SPECT reconstruction that will not require an additional transmission scan (such as the CT scan) for attenuation compensation. For more […]


Our lab has been awarded the NVIDIA GPU grant! NVIDIA will provide us state-of-the-art Quadro P6000 card. Armed with 3,840 CUDA parallel processing cores, a peak single-precision performance of 12 TFLOPS, and a 24 GB GPU memory, this card will provide an excellent high-performance computing platform for several computational medical imaging solutions that we are […]

New paper on reconstruction method for FMT brain imaging

Our paper on developing a new reconstruction method for fluorescence molecular tomography in the context of transcranial imaging has been published in Biomedical Optics Express. The paper demonstrates that accurately modeling noise in FMT while accounting for sparsity leads to improved reconstruction performance!

Abstract on deep learning for PET image analysis accepted @ SNMMI

Our abstract titled “A deep-learning-based fully automated segmentation approach to delineate tumors in FDG-PET images of patients with lung cancer” was accepted for an oral presentation at the 2018 SNMMI Annual Meeting. In this work, we developed and demonstrated the efficacy of a deep learning-based method for tumor segmentation in PET images. Since these images are […]

New paper on modeling photon propagation for optical imaging

Our paper on incorporating reflection boundary conditions in the radiative transport equation for modeling photon transport has been accepted for publication in Biomedical Optics Express.  Computational studies show that method yields an average of 84% more accurate estimate of the optical coefficients in comparison to when the reflection boundary conditions are not modeled! This paper continues our […]

Joining WashU as Assistant Professor of BME/Radiology

Dr. Abhinav Jha will be joining Washington University in St. Louis as an Assistant Professor of Biomedical Engineering in the School of Engineering and Applied Sciences and of the Mallinckrodt Institute of Radiology at the School of Medicine starting April 2018. His recruitment is part of the Imaging Sciences Initiative at WashU.

Dr. Jha invited to SNMMI/NCI Round Table discussion

Dr. Abhinav Jha was invited to a round table discussion on Targeted Radiotherapy: From Research to Clinical Practice. The discussion was organized by the Society of Nuclear Medicine and Molecular Imaging (SNMMI) and the National Cancer Institute’s NCI) at the Smilow Translational Research Building at the University of Pennsylvania, Philadelphia.  

Dr. Jha co-chairs session at Computational Phantoms Workshop

Dr. Abhinav Jha co-chaired a session at the 6th International Workshop on Computational Human Phantoms, Annapolis, MD ( This workshop has been focusing on the exciting field of computational phantoms being developed for medical imaging. This year, there was a special emphasis on the applications of these phantoms in computational modeling and simulations for biomedical imaging, radiation dosimetry, […]

Three articles on developing observers for myocardial SPECT

Optimizing myocardial perfusion SPECT systems and methods for perfusion defect detection is highly significant. While mathematical observers exist for this purpose, they do not account for the variability in cardiac defect characteristics. In a series of articles, we investigate the causes for this issue and propose a novel mathematical observer that addresses this issue. X. […]

Young Investigator Award at SNMMI 2017

Dr. Abhinav Jha was awarded a Therapy Center for Excellence Young Investigator Award at the Society of Nuclear Medicine and Molecular Imaging (SNMMI) Annual meeting 2017. The award was for the paper titled “A no-gold-standard framework to evaluate FDG-PET tumor-segmentation methods on the task of measuring prognostic biomarkers for lung-cancer treatment” (link). We also had another […]

Two new journal articles on clinical quantitative PET

Metrics derived from quantitative PET, in particular intra-tumor heterogeneity, have sparked considerable interest as biomarkers for prognosis and predicting therapy response. In collaboration with radiologists at the Division of Nuclear Medicine, we have been investigating the role of intra-tumor heterogeneity in patients with different cancers. We recently published a couple of articles based on our research, […]

New paper on no-gold-standard evaluation in JMI Special section

Our paper on developing a no-gold-standard (NGS) technique to evaluate quantitative imaging methods with patient data in the absence of ground truth was accepted for publication in a special section of the Journal of Medical Imaging (link). This work was in collaboration with radiologists at the Johns Hopkins Division of Nuclear Medicine. We were interested […]

Three talks at SNMMI Annual Meeting 2017

We have had three talks accepted for presentation at the Society of Nuclear Medicine and Molecular Imaging (SNMMI) Annual Meeting 2017. A. K. Jha, C. Marcus, R. Wray. R. Subramaniam, and E. Frey, “A no-gold-standard framework to evaluate FDG-PET tumor-segmentation methods on the task of measuring prognostic biomarkers for lung-cancer treatment”, Therapy Center Young Investigator Award, […]

New article on ADC estimation in diffusion MRI

Our paper on developing a statistical technique to estimate a single ADC value from a lesion using diffusion MRI was recently published in the journal Magnetic Resonance in Medicine. Especially exciting that the proposed method was rigorous, computationally fast, easy-to-implement, convenient-to-use, and more accurate than state-of-the-art methods in clinical settings! This work was in collaboration with […]