Modeling in Scientific Imaging and Visualization Laboratory (MOTIV)

Modeling in Scientific Imaging and Visualization Laboratory (MOTIV)

In the last years, there has been a growing interest in the use of digital images as a tool to support assessment and decision-making. This can be seen in diverse areas such as, medicine (MRI, computerized tomography scanner, ultrasound) as a mean to support clinical diagnosis, remote sensing for natural and urban covers (forest yield and productivity, crop predictors, precision agriculture, urban planning), astronomy for scientific purposes (e.g., supernova detection, galaxy classification, signals reconstruction), biology in the study of cellular processes (e.g., the study of intracellular dynamics) and human perception modeling (camouflage assessment and design).

Moreover, the development of new technologies both image acquisition and computational capacity (High Performance Computing), have allowed a major breakthrough in the treatment field of digital imaging.

In this sense, CMM decided to create the Laboratory of MOdeling in scienTific Imaging and Visualization (MOTIV), whose mission is responding to different questions in the field of digital images, coming from scientific, industrial and public areas.

General Objective:

  • Develop or adapt image-processing tools to solve problems from the scientific, industrial and public players.

Specific objectives:

  • To develop new mathematics for image processing and visualization.
  • To implement computational tools to answer requirements coming from different areas related to digital images.
  • To generate a meeting point for discussion, between researchers from different fields (biologists, physicians, engineers, physicists and mathematicians), having a common interest in the area of the digital images.
  • To create human capital with expertise in advanced analysis and processing of digital images.

Research Areas

The main areas of applications are the following:

  • Biomedical Images: Focusing on the analysis of medical images (MRI, scanner, ultrasound), which are used as a diagnostic tool for the patient and for surgery planning, as well as biological images (both intracellular and extra-cellular), which allow the study of different biological phenomena.
  • Earth Observation and Modeling: Includes the use of images obtained through remote sensing, both active (radar and LIDAR) and passive (satellite images) for evaluation and monitoring of land cover, such as natural resources, urban planning, among others.
  • Human Perception Modeling: In this case we are interested in to consider algorithms for human vision modeling, like retina, and their applications. One of these applications is to create indexes for the evaluation of camouflage
  • Astronomical Images: With the arrival of the new astronomical projects (VLT, E-ELT, ALMA), it is necessary to automatize some images processing procedures. In particular we begin to study some problems related to the reconstruction of images and denoising.


  • Jaime H. Ortega, Ph. D. in Applied Mathematics, Universidad Complutense de Madrid, Spain. Lab Director.
  • Takeshi Asahi, Ph. D. in Engineering, Yokohama National University, Japan. Scientist.
  • Raúl Gouet, Docteur Ingénieur, U. de Paris, Orsay, France. Researcher
  • Fernando Padilla, Forest Engineer, U. de Chile, Chile. Minor in Geomatics. Researcher.
  • Cyndi Durán, Natural Renewable Resources Engineer, U. de Chile, Chile. Project Engineer.
  • Rodrigo Lecaros, Civil Mathematical Engineer, U. de Chile, Chile. Ph. D. Student.
  • Alfredo López, Civil Mathematical Engineer, U. de Chile, Chile. Ph. D. Student.
  • Matías Godoy, Civil Mathematical Engineer (c), U. De Chile, Project Engineer.


MOTIV team