Patch-MI 2015 - Patch-based Technique in Medical Imaging

Patch-based technique plays an increasing role in the medical imaging field, with various applications in image segmentation, image denoising, image super-resolution, computer-aided diagnosis, image registration, and abnormality detection and image synthesis. For example, patch-based approaches using training library of annotated atlas have been the focus of many attentions in segmentation and computer-aided diagnosis. It has been shown that patch-based strategy learns from examples to produce an accurate representation of data, while the use of training library enables to easily provide prior knowledge to the model. As an intermediate level between global image and localized voxel, patch-based models offer an efficient and flexible way to represent very complex anatomies.
The main aim of this workshop is to help advance the scientific research within the broad field of patch-based processing in medical imaging. This workshop will focus on major trends and challenges in this area, and it presents work aimed to identify new cutting-edge techniques and their use in medical imaging. We hope the workshop to become a new platform for translating research from bench to bedside. We are looking for original, high-quality submissions on innovative research and development in the analysis of medical image data using patch-based technique.
Accepted papers will be published in LNCS proceeding.
Topics
Topics of interests include but are not limited to patch-based processing dedicated to:
Image segmentation of anatomical structures or lesions (e.g., brain segmentation, cardiac segmentation, MS lesions detection, tumor segmentation)
Image enhancement (e.g., denoising or super-resolution dedicated to fMRI, DWI, MRI or CT)
Computer-aided prognostic and diagnostic (e.g., for lung cancer, prostate cancer, breast cancer, colon cancer, brain diseases, liver cancer, acute disease, chronic disease, osteoporosis)
Mono and multimodal image registration
Multi-modality fusion (e.g., MRI/PET, PET/CT, projection X-ray/CT, X-ray/ultrasound) for diagnosis, image analysis and image guided interventions
Mono and multi modal image synthesis (e.g., synthesis of missing a modality in a database using an external library)
Image retrieval (e.g., context-based retrieval, lesion similarity)
Dynamic, functional, physiologic, and anatomic imaging
Super-pixel/voxel in medical image analysis
Sparse dictionary learning and sparse coding
Analysis of 2D, 2D+t, 3D, 3D+t and 4D and 4D+t data
Academic Objectives
An academic objective of the workshop is to bring together researchers in medical imaging to discuss new techniques using patch-based approaches and their use in clinical decision support and large cohort studies. Another objective is to explore new paradigms of the design of biomedical image analysis systems that exploit latest results in patch-based processing and exemplar-based method. MICCAI-PMI 2015 will feature a single-track workshop with keynote speakers, technical paper presentations, poster sessions, and demonstrations of the state-of-the-art technics and concepts that are applied to analyzing medical images.