High-performance cloud computing (HPCC) is an integration of high-performance computing (HPC) with cloud computing that provides an alternative informatics infrastructure to deliver the supercomputer power needed for developing and reading high quality, multidimensional diagnostic images on desktop or mobile devices. Such infrastructure would advance the use of high-throughput cancer screening like virtual colonoscopy (VC), also known as computed tomography colonography (CTC). The goals of this proposal are to develop and validate the clinical benefits of a mobile HPCC-Virtual Colonoscopy decision support system (HPCC-VC) that integrates novel high-performance electronic cleansing and computer-aided detection schemes. The combination of high performance electronic cleansing (hpEC) with high performance computer aided detection (hpCAD) will allow visualization of the entire mucosal surface of the colon without artifact. Specifically, we hypothesize that the mobile HPCC-VC system will improve the quality of electronic cleansing of non-cathartic CTC (ncCTC) images, will deliver images 100 times faster than conventional approaches, and will improve reader performance in the detection of colonic lesions in the images analyzed on mobile high-resolution display devices. To achieve these goals, an HPCC platform will be established by use of a CPU-cluster-based supercomputing and parallel image processing libraries. Then, an hpEC scheme will be developed that effectively removes the residual fecal materials in ncCTC images. In parallel, a high-resolution hpCAD scheme will be developed to support high-performance detection of colonic lesions in ncCTC. These schemes will be integrated into a mobile HPCC-VC system on the HPCC platform. Necessary preliminary studies in the development of computed EC and CAD schemes show promise; and the development and deployment of the HPCC platform will advance the quality, speed, and utility of high performance, multidimensional imaging for colon cancer screening. A comprehensive reader performance study will be conducted to determine the clinical application and benefit of images analyzed and delivered through an HPCC platform. Successful development of HPCC-VC will demonstrate the clinical benefit of the platform for improved diagnostic imaging and facilitation of accurate, high-throughput colon cancer screening that is highly acceptable to patients. In the longer term, broad adoption and use of the HPCC-VC system will facilitate early and accurate diagnoses, and thus reduce mortality from colon cancer.
Successful development of the HPCC-VC system will demonstrate the clinical benefit of HPCC platform for diagnostic imaging, and will provide a high-throughput colon cancer screening scheme for colorectal lesions that is highly acceptable to patients and highly accurate. Such a system will promote the early diagnosis of colon cancer, and ultimately reduce the mortality due to colon cancer.
|Tachibana, Rie; Näppi, Janne J; Ota, Junko et al. (2018) Deep Learning Electronic Cleansing for Single- and Dual-Energy CT Colonography. Radiographics 38:2034-2050|
|Tachibana, Rie; Näppi, Janne J; Kim, Se Hyung et al. (2015) Electronic cleansing for dual-energy CT colonography based on material decomposition and virtual monochromatic imaging. Proc SPIE Int Soc Opt Eng 9414:94140Q|
|Näppi, Janne J; Regge, Daniele; Yoshida, Hiroyuki (2015) Context-specific method for detection of soft-tissue lesions in non-cathartic low-dose dual-energy CT colonography. Proc SPIE Int Soc Opt Eng 9414:94142Y|
|Nasirudin, Radin A; Tachibana, Rie; Näppi, Janne J et al. (2015) A comparison of material decomposition techniques for dual-energy CT colonography. Proc SPIE Int Soc Opt Eng 9412:|
|Tachibana, Rie; Näppi, Janne J; Yoshida, Hiroyuki (2014) Application of Pseudo-enhancement Correction to Virtual Monochromatic CT Colonography. Abdom Imaging (2014) 8676:169-178|
|Näppi, Janne J; Tachibana, Rie; Regge, Daniele et al. (2014) Information-Preserving Pseudo-Enhancement Correction for Non-Cathartic Low-Dose Dual-Energy CT Colonography. Abdom Imaging (2014) 8676:159-168|
|Yoshida, Hiroyuki; Wu, Yin; Cai, Wenli (2014) Analysis of scalability of high-performance 3D image processing platform for virtual colonoscopy. Proc SPIE Int Soc Opt Eng 9039:90390U|
|Näppi, Janne J; Do, Synho; Yoshida, Hiroyuki (2013) Computer-Aided Detection of Colorectal Lesions with Super-Resolution CT Colonography: Pilot Evaluation. Abdom Imaging (2013) 8198:73-80|
|Yoshida, Hiroyuki; Wu, Yin; Cai, Wenli et al. (2012) Scalable, high-performance 3D imaging software platform: system architecture and application to virtual colonoscopy. Conf Proc IEEE Eng Med Biol Soc 2012:3994-7|