Detection of Lung Nodules via Deep Learning in Micro-CT

Detection of Lung Nodules in Micro-CT Imaging Using Deep Learning
Matthew D. Holbrook; Darin P. Clark; Rutulkumar Patel; Yi Qi; Alex M. Bassil; Yvonne M. Mowery; Cristian T. Badea
Tomography 2021, Volume 7, Issue 3, 358-372

Data and Code Availability: The data presented in this work are available by request at, and the code used for training and analysis can be found at

Tumor Mapping

Our tumor mapping paper  is now published and our images made the cover:

Blocker SJ et al. Ex Vivo MR Histology and Cytometric Feature Mapping Connect Three-dimensional in Vivo MR Images to Two-dimensional Histopathologic Images of Murine Sarcomas.

Radiol Imaging   Cancer 2021 May;3(3):e200103. doi: 10.1148/rycan.2021200103

Protocol on the Primary Sarcoma Model

Our p53/MCA High Mutational Load Model of Soft Tissue Sarcoma
Dr. Yvonne Mowery

To recapitulate human soft tissue sarcoma (STS)  in the preclinical setting of our co-clinical trial, we generate a primary mouse model of STS by intramascular injection of adenovirus containing Cas9 gene and a guide RNA targeting p53 gene (Adeno-Cas9-sgRNAp53) and carcinogen 3-methylcholanthrene (MCA) into the gastrocnemius muscle of wild-type 129/SvJ mice. This is describe in:

Primary Sarcoma Model Protocols – Ad-Cre or Ad-sgp53-Cas9 Intramuscular Injection

Towards deep learning detection of lung nodules using micro-CT data

New CIRP network publication!

Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine. Shoghi KI, Badea CT, Blocker SJ, Chenevert TL, Laforest R, Lewis MT, Luker GD, Manning HC, Marcus DS, Mowery YM, Pickup S, Richmond A, Ross BD, Vilgelm AE, Yankeelov TE, Zhou R. Tomography. 2020 Sep;6(3):273-287. doi: 10.18383/j.tom.2020.00023.

MRI-Based Deep Learning Segmentation and Radiomics of Sarcoma

We have created an image processing pipeline for high-throughput, reduced-bias segmentation of multiparametric tumor MRI data and radiomics analysis, to better our understanding of preclinical imaging and the insights it provides when studying new cancer therapies.

Link to our new paper

The impact of respiratory gating

As part of our co-clinical trial studying immunotherapy and radiotherapy in sarcomas, we are using micro-CT of the lungs to detect and measure metastases as a metric of disease progression. In this study, we have addressed the impact of respiratory gating during micro-CT acquisition on improving lung tumor detection and volume quantitation.

S. J. Blocker,M. D. Holbrook,Y. M. Mowery,D. C. Sullivan,C. T. Badea, The impact of respiratory gating on improving volume measurement of murine lung tumors in micro-CT imaging,

Our PLOS ONE paper is now published!

Bridging the translational gap: Implementation of multimodal small animal imaging strategies for tumor burden assessment in a co-clinical trial
S. J. Blocker, Y. M. Mowery, M. D. Holbrook, Y. Qi, D. G. Kirsch, G. A. Johnson, C. T. Badea,  PLoS ONE 14(4): e0207555. (2019)

U24 DICOM tool

Download our U24 DICOM tool

This is a MATLAB-based tool for converting 3D CT image volumes from NifTi format to DICOMs. This repository contains a GUI which can be used to assign values to common DICOM fields. It also contains functions which can be used in your own code to streamline workflows.

Duke Standard Operating Procedure for MR Imaging at 7T of tumor-bearing mice using a surface coil

Generalized Scanning Protocol (U24) – SOP

This SOP is designed as a general guide for in vivo MR imaging of small animals as part of a pre-clinical cancer study, using a volume transmit coil + surface receive coil at high fields. Note that this protocol begins with information that is not machine or project specific.