• [2015-10-20] Program is now avialble.
  • [2015-10-08] Information about invited talks is updated.
  • [2015-09-14] The submission deadline is extended to 20th September.
  • [2015-09-09] Submission open (Submit via EasyChair).
  • [2015-09-07] Information about paper submission is updated.
  • [2015-07-09] Information about submission is updated.
  • [2015-05-13] The list of program committee members is added.
  • [2015-03-01] Website opened.
Call for Papers

The workshop on mathematical and computational methods in biomedical imaging and image analysis (MCBMIIA2015) focuses on mathematical and computational aspects of biomedical imaging and image analysis and on these relations to computer vision. We call for papers for applications of the methods to anatomy, autopsy, biopsy, physiology and nano-biology. The expected areas for contributions are following. But all aspects of mathematical treatment medical imaging and image analysis are welcome.
  • Syntactical and combinatorial methods for biomedical imaging and image analysis
  • Statistical and probabilistic methods for biomedical imaging and image analysis
  • Variation al and combinatorial optimisations for biomedical imaging and image analysis
  • Discrete and digital geometry and topology for biomedical image analysis
  • Inverse methods for biomedical imaging and image analysis
  • Theoretical aspects of multimodal biomedical image analysis
  • Numerical and computational aspects of biomedical imaging and image analysis
  • Graphics and mesh generation for biomedical imaging and image analysis
  • Machine learning in biomedical imaging and image analysis
  • Applications to computational anatomy, autopsy, biopsy, physiology and nano-biology
In biomedical imaging and image analysis, the researches aim to design systems that assist medical doctors. In contrast, in computer vision researches focus construct machines that see. The forum aims to derive a bridge on this gap from the viewpoints of mathematical and computational aspects in computer vision.

Important Dates

Submission deadline 20th September, 2015
Author notification 5th October, 2015
Camera-ready 21th October, 2015
Workshop 24th November, 2015

Paper Submission

The submission policy of the MCBMIIA2015 follows to the PSIVT2015 main conference. For details see here. The maximum of pages in free of charge is 12 pages in LNCS style. If you will pay 100NZD/Page, you can add at most 2 pages. See main conference page.

The MCBMIIA2015 submission site is managed by EasyChair Conference System.

Program Committee Members

General Chair

  • Hidekata Hontani (Japan)


  • Michael Cree (New Zealand)
  • Krim Hamid (USA)
  • Atsushi Imiya (Japan)

Committee Members

Andreas Aplers (Germany)
David Coeurjolly (France)
Michel Couprie (France)
Aasa Feragen (Denmark)
Hamid Gholamhosseini (New Zealand)
Chun-Rong Huang (Taiwan)
Xiaoyi Jiang (Germany)
Yukiko Kenmochi (France)
Antonio M. López (Spain)
Yoshitaka Masutani (Japan)

Kensaku Mori (Japan)
Yoshito Otake (Japan)
Xue-Cheng Tai (Norway)
João Manuel R. S. Tavares (Portugal)
Seiichi Uchida (Japan)
Martin Welk (Austria)
Burkhard Wuensche (New Zealand)
Otmar Scherzer (Austria)
Nataša Sladoje (Serbia)

System Administrators

The following students work as system administrators to maintenance this website and to handle paper submission system.
  • Hayato Itoh (Japan)
  • Ryo Sasaki (Japan)
Invited Talk

Morning session

  • Hamid Gholamhosseini (AUT, New Zealand)
    "Melanoma Image Processing and Analysis for Decision Support Systems"

    Melanoma is the most aggressive form of skin cancer which is responsible for the majority of skin cancer related deaths. Image processing and analysis of melanoma images can result in (better) detection and early diagnosis and therefore reducing the mortality rate.
    Efficient pre-processing, image enhancement, segmentation, feature extraction and classification techniques have been developed to improve the performance of Computer Aided Diagnosis (CAD) of melanoma images. Border detection of lesions in melanoma images is important in improving the accuracy of CAD systems in detecting melanoma. We have developed a semi-automated algorithm to discriminate the foreground lesion from skin background by clicking on a small subset of the lesion.
    Implementing the image processing and analysis algorithms for CAD and decision support systems is computationally demanding. However, due to high inherent parallelism of such algorithms, systems with parallel processors could be useful for accelerating but they are energy intensive and costly.
    Special reconfigurable hardware such as Field-Programmable Gate Arrays (FPGAs) with powerful parallel processing feature can be used for achieving necessary performance of embedded systems with efficient utilization of hardware resources. In order to achieve acceleration of the image processing and analysis algorithms, we implement the most compute-intensive algorithms of the CAD and decision support systems onto FPGA for deploying as an embedded device.
    A hardware/software co-design approach was proposed for implementing Support Vector Machine (SVM) classifier for classifying melanoma images online. The hybrid Zynq platform was used for implementing the proposed classifier using High Level Synthesis design methodology. The implemented SVM classification system on Zynq demonstrated high performance with low resource utilization and power consumption, meeting several embedded systems constraints.
    Overall, the hardware implementation on FPGA could be extended in the future for other computationally demanding parts in the process, aiming to reach an efficient real-time decision support system for enhancing early detection of melanoma with high performance and low cost.
  • Akinobu Shimizu (Tokyo University of Agriculture and Technology, Japan)
    "Segmentation of Organs with Atypical Shapes and/or Large Pathological Lesions from Medical Volumes"

    This study focuses on automated segmentation algorithms for an organ with an atypical shape and/or large pathological lesions. First, a sparse modeling based approach with lesion basis is presented for an organ with an atypical shape and large pathological lesions in a computed tomography (CT) volume. Second, a relaxed conditional statistical shape model (SSM) is presented to manage errors in conditions that involve an irregular shape of an organ and/or lesions. A sequentially graph cuts based segmentation algorithm with the relaxed conditional SSM is presented to show the effectiveness of such an SSM in segmentation. Third, algorithms for developing the SSMs and segmentation algorithms for postmortem imaging, in which the CT values and shapes of organs were significantly changed due to postmortem changes, are presented. Finally, future directions for segmentation in medical imaging will be presented with recent progresses of our research group, which include multi-shape graph cuts and fusion between an SSM and graph cuts.

Afternoon session

  • Hiroshi Ishikawa (Waseda University, Japan)
    "Higher-Order Graph Cuts and Medical Image Segmentation"

    Energy minimization is regularly used for medical image segmentation. Higher-order energies are perhaps not as common, but are nevertheless being used increasingly often. Whereas the common first order (pairwise) potential can directly model only the relationship between pairs of pixels, the higher-order potential can model more complex and useful relationships between more than two variables. For instance, sets of pixels, chosen according to the shape to be segmented, can be encouraged to be entirely in one segment or the other by higher-order terms. In this talk, I will describe methods for minimizing higher-order energies using graph cuts as well as some real-world examples of their applications in medical image segmentation that have been deployed in commercial medical imaging software.
  • John Rugis (University of Auckland, New Zealand)
    "Realistic 3D Cell Modelling for FEM Simulation"

    We describe the latest results from an interdisciplinary project that encompasses a range of activities targeting anatomical data based structural modelling of individual salivary cell clusters, solution of cellular calcium dynamics function in full 3D simulations and interactive visualization of resultant calcium waves. Real biological samples were digitized using fluorescent markers and confocal microscopy. A set of image slices was used as the basis for a full 3D graphics model reconstruction of one cluster of cells. This anatomically correct model was used in turn as the basis for the creation of a 3D tetrahedral mesh suitable for finite element simulations. The same underlying 3D graphics mesh was used in the animated visualization of the calcium concentration simulation time series results. This work was conducted in collaboration with James Sneyd and Shawn Means from the Department of Mathematics at the University of Auckland and with David Yule from the School of Medicine and Dentistry at the University of Rochester.

Best Paper Award

The MCBMIIA2015 will award the best paper of the workshop, voted by the program committee.