Automated Techniques for multiscale Image and Signal Processing

Prof. Filippo Molinari

Current Position

 

Associate Professor of Bioengineering on faculty of the Dept. of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy, since October 2014.

 

Areas of Interest

  •  Ultrasound technology: cardiovascular imaging, photoacoustic imaging, texture analysis, vascular analysis of cancer lesions
  •  Imaging: image segmentation architectures, microscopy imaging, image rendering and reconstruction
  •  Neuroimaging: fMRI, development of near-infrared spectroscopy (NIRS) systems and NIRS signal processing; minimally-invasive multiple sclerosis assessment and monitoring
  •  Signal processing: time-frequency analysis, non-linear analysis, empirical mode decomposition 

Recent works and ongoing studies

  •  Long-term monitoring of ozone autohemotherapy effects in multiple sclerosis patients
  •  Automated measurement of the IMT and atherosclerosis monitoring by imaging techniques
  •  3-D vascular reconstruction of cancer networks by contrast-enhanced ultrasound images
  •  Quantitative microscopy imaging in breast cancer, prostate cancer, and liver transplants

 

Keywords

 

Image processing, Image segmentation, Image rendering and reconstruction, Ultrasounds, Near-infrared spectroscopy, Neuroimaging, Time – frequency transforms

 

Research interests

 

Prof. Filippo Molinari spent over 10 years in developing advanced data analysis techniques in several fields of biomedical engineering, including neurophysiology, neurorehabilitation, vascular analysis, functional imaging, and neuromuscular assessment. He is active in the field of ultrasound image processing, where he developed innovative algorithms for the completely automated segmentation and characterization of the carotid artery. He is also active in the field of neuroscience and, particularly, in the non-invasive monitoring and assessment of cerebral functions and autoregulation.

 

Image processing – Prof. Molinari is the principal investigator of the Image Processing division of the Biolab of the Politecnico di Torino. The main activity focus is the development of fully automated algorithms for quantitative imaging. From a technical point of view, Prof. Molinari developed original techniques based on robust edge-detectors, deformable models, and multiresolution operators. The principal recent applications are:

 

· Ultrasound cardiovascular imaging: automated measurement of the intima-media thickness of arteries; non-invasive characterization of atherosclerotic plaque; arterial wall aging and strain measurement.

 

· Cancer imaging: quantification of cancer lesions’ vascular pattern; automated segmentation and classification of suspicious lesions (thyroid and ovarian); automated processing of histological, fluorescence, and immunohistochemical images; cell counting and stereological analysis; automation of the workflow in pathology.

 

· Muscoloskeletal ultrasound imaging: automated measurement of muscle thickness, fascicles length and pennation angles; texture analysis of skeletal muscles; force estimation in dynamic contractions.

 

Signal processing - Prof. Molinari has been working in the field of biomedical signal processing since 15 years. His main activity is the development of innovative time-frequency, non-linear processing strategies, and empirical-mode decomposition of biological signals. The main recent applications are:

 

· Functional analysis of brain metabolism by near-infrared spectroscopy in patients with neurodegenerative disorders.

 

· Aging assessment by analysis of muscle fatigue, muscle metabolism and EMG.

 

 

 

 Further details about prof. Molinari’s research can be found at the following link:

 http://socrate.polito.it/biolab/Research.html

 

 

Publications

 

Prof. Molinari published more than 130 contributes including journal papers and peer reviewed proceedings in the field of signal and image processing, including four collaborative books. A complete list of prof. Molinari publications can be found at the following link:

http://porto.polito.it/view/creators/Molinari=3AFilippo=3A009675=3A.html

 

The updated Google Scholar profile of Prof. Molinari can be found at the following link:

http://scholar.google.it/citations?user=ttbUYiQAAAAJ&hl=it