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10 years of news and resources for members of the IEEE Signal Processing Society
By Deniz Erdoğmuş (Liaison to eNews for the BISP TC)
The BioImaging and Signal Processing Technical Committee (BISP TC) of the IEEE Signal Processing Society (IEEE-SPS) promotes activities within the broad technical areas of biomedical and biological signal and image processing. Specific fields of interest include (but are not limited to): molecular and medical imaging, microscopy, signal processing in computational biology and biological networks, signal processing of physiological signals, and bioinformatics.
The IEEE International Symposium on Biomedical Imaging (ISBI) 2013 will be held at the Westin San Francisco Market Street, San Francisco, CA, USA. ISBI is a premier interdisciplinary conference encompassing all scales of imaging in medicine and the life sciences. The 2013 meeting will continue its tradition of fostering knowledge transfer between different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observations. ISBI is a joint initiative from the IEEE Signal Processing Society (SPS) and the IEEE Engineering in Medicine and Biology Society (EMBS). The 2013 meeting will open with a morning of tutorials, followed by a scientific program of plenary talks, invited special sessions, challenges, as well as oral and poster presentations of peer-reviewed papers. The 2013 edition is shaping up to be a very exciting event! It will feature a selection of renowned plenary speakers, including Simon Cherry (UC Davis), David Donoho (Stanford), John Sedat (UC San Francisco), Joe Gray (Oregon Health Sciences Institute), and Stephen Wong (Methodist Hospital Research Institute). Prospective authors have submitted some 680 4-page papers, which are undergoing peer-review. ISBI'13 will again feature a series of Challenges in which entrants will be able to quantitatively compare competing approaches on common data sets to push the limits on some of the most important biological and medical image processing problems. In addition, the conference will support special sessions and tutorials on deep learning to advances in medical imaging. To encourage attendance by a broader audience of imaging scientists (in particular from the biology and physics community) and offer additional opportunities for cross-fertilization. ISBI again proposes a second track featuring posters selected from abstract submissions without subsequent archival publication. The deadline for abstracts is December 7th. Spread the word!
The BISP TC recently conducted its annual elections. Michael Liebling is elected as the Vice Chair of Elections as well as being elected for a renewed term of membership. Philippe Ciuciu, Nevenka Dimitrova, Synho Do, Miguel Gonzales-Ballester, Maria Ledesma Crbayo, Li Pan, Otaf Ronneberger, Hamid Soltanian-Zadeh, Carlos, Sanchez-Sorzano, Jong Ye, Laure Blanc-Feraud, and Mathews Jacob were also elected as members to the committee. Erhan Bas and Thomas Walter were elected as associate members.
The BISP TC asks you to mark your calendars for the 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), to be held in Vancouver, Canada on May 26-31, 2013. ICASSP is the largest technical conference focused on signal processing and its applications, including those in biomedicine.
BISP TC member Ilya Shmulevich has recently co-chaired The Cancer Genome Atlas Second Annual Scientific Symposium that took place in Crystal City, VA, USA on Nov 27-28, 2012.
BISP TC member Joao Sanchez is the general chair of the upcoming Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2013), which will take place in Madeira, Portugal on June 5-7, 2013.
BISP TC member Paul Yushkevich, with his teammates Hongzhi Wang and Brian Avants, won first place in the 2012 Grand Challenge on Multi-Atlas Labeling held as part of the 2012 International Conference on Medical Image Computing and Computer Aided Intervention (MICCAI'2012). The team's algorithm, which employs joint label fusion with learning-based error correction, achieved top accuracy and test-retest reliability among 25 submissions for labeling 140+ anatomical structures in magnetic resonance images of the human brain.
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