CIBT 2010

MICCAI 2010 Workshop on Computational Imaging Biomarkers for Tumors: From Qualitative to Quantitative - September 20, 2010



09:00-09:10Opening speech by one of the organizers

09:10-09:55Invited talk 1:
Theory and Applications of Image-Based Predictive Control of Prostate Cancer Surgery and Experimental Validation in Vivo
Prof. Yusheng Feng, The University of Texas at San Antonio

09:55-10:20Oral presentation 1
Modelling Tumor Cellularity in Newly Diagnosed GBMs Using MR Imaging and Spectroscopy
Alexandra Constantin, Sarah Nelson and Ruzena Bajcsy (paper 2)

10:20-10:45Tea break

10:45-11:30 Invited talk 2
A Label Free Approach for Molecular Imaging Guided Diagnosis and Therapy
Prof. Stephen T. Wong, The Methodist Hospital Research Institute

11:30-11:55Oral presentation 2
Biomarker Detection in Whole Slide Imaging Based on Statistical Color Models
Jie Shu, Guoping Qiu, Mohammad Ilyas, et al (paper 4)

11:55-12:20Oral presentation 3
Atlas to Image-with-Tumor Registration Based on Demons and Deformation Inpainting
Hans Lamecker and Xavier Pennec (paper 1)

12:20-13:30Lunch break

13:30-14:15Invited talk 3
Ultra-low Dose CT Imaging for Cancer Radiotherapy
Prof. Steve B. Jiang, University of California, San Diego

14:15-14:40Oral presentation 4
Validation of Liver Tumor Segmentation in CT Scans by Relating Manual and Algorithmic Performance - A Preliminary Study
Jan Hendrik Moltz, Jan Rühaak, Christiane Engel, et al (paper 5)

14:40-15:05Oral presentation 5
Localization of Language Areas in Brain Tumor Patients Based by Functional Geometry Alignment
Georg Langs, Yanmei Tie, Laura Rigolo, et al (paper 3)

15:05-15:30Tea break

15:30-16:15Invited talk 4
Title: to be announced
Prof. Simon K. Warfield, Harvard Medical School and Children's Hospital, Boston

16:15-16:40Oral presentation 6
Automatic Classification of Glioma Subtypes and Biomarker Identification Using DESI Mass Spectrometry Imaging
Vandana Mohan, Nathalie Agar, Ferenc Jolesz, et al (paper 6)

16:40-17:00Discussion and sharing

17:00Closure of the workshop

Invited Talks

Speaker 1: Prof. Yusheng Feng
Computational Bioengineering and Control Lab
Department of Mechanical Engineering
The Univeristy of Texas at San Antonio

Title: Theory and Applications of Image-Based Predictive Control of Prostate Cancer Surgery and Experimental Validation in vivo


Advances in computational sciences and imaging techniques have shown unprecedented potential to assist oncologists, radiologists, and surgeons by providing advanced computational models for biological studies and clinical applications such as model-based treatment outcome prediction and image-guided control in real-time. Recently, we have demonstrated, in collaboration with UT Austin and M.D. Anderson Cancer Center in Houston, that MR temperature imaging (MRTI) guided laser therapy can be modulated by predictive real-time control on in vivo canine prostate with high precision. In this talk, I will discuss the main ideas of a general computational infrastructure that consists of modules for image analysis tools for treatment planning, 3D numerical model generation from MRI scan for treatment optimization, and a systematic approach to calibrate and modulate laser surgery through predictions of computational models. The in vivo experiments show that the damage zone of tumor regions detected from MRI coincide very well with images taken after the treatment. Other modules in the computational framework permit predictions of cellular and tissue response to thermal therapy, as well as applications in treatment planning and surgical control.

Speaker 2: Prof. Stephen T. Wong
Center for Bioengineering and Informatics
The Methodist Hospital Research Institute

Title: A Label Free Approach for Molecular Imaging Guided Diagnosis and Therapy

Abstract: N/A

Speaker 3: Prof. Steve B. Jiang
Department of Radiation Oncology
University of California, San Diego

Title: Ultra-low Dose CT Imaging for Cancer Radiotherapy


Cone-beam computed tomography (CBCT) has been broadly used in image guided radiation therapy (IGRT) and adaptive radiation therapy (ART), to acquire the updated patient's geometry for precise targeting and treatment adaptation. However, the repeated use of CBCT during a treatment course has raised a serious concern on excessive x-ray imaging doses delivered to patients, which has greatly limited the maximal exploitation of the potential of modern radiotherapy. Especially for pediatric patients, this concern has prohibited the use of IGRT and ART, leading to compromised treatment outcome. Advanced iterative reconstruction algorithms, based on compressed sensing techniques, have demonstrated tremendous power in reconstructing CBCT images from very few and/or noisy projections, resulting in dramatically reduced imaging dose. However, these algorithms are very computationally inefficient and thus cannot be used in most clinical applications. We have recently developed an innovative CBCT reconstruction algorithm with a mathematical structure perfect for parallelization on a graphics processing unit (GPU) platform. Our preliminary results have shown that we can improve the efficiency by a factor of 100 over existing iterative algorithms and reduce the imaging dose by factor of 40~100 compared to the current clinical standard. Similar algorithms have also been used for ultra-low dose CT, 4DCT, helical CT and 4D CBCT reconstruction.

Speaker 4: Prof. Andrew K. Warfield
Department of Radiology
Harvard Medical School and Children's Hospital, Boston

Title: to be announced

Abstract: N/A