Biomedical image time series registration with particle filtering Parçacik süzgeci ile biyomedikal görüntü zaman serisi çakiştirma
2013 21st Signal Processing and Communications Applications Conference, SIU 2013, Haspolat, Türkiye, 24 - 26 Nisan 2013, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/siu.2013.6531501
- Basıldığı Şehir: Haspolat
- Basıldığı Ülke: Türkiye
- Anahtar Kelimeler: Bayesian filtering, Biomedical image registration, Neural image analysis
- Boğaziçi Üniversitesi Adresli: Evet
Özet
We propose a family of methods for biomedical image time series registration based on Particle filtering. The first method applies an intensity-based information-theoretic approach to calculate importance weights. An effective second group of methods use landmark-based approaches for the same purpose by automatically detecting intensity maxima or SIFT interest points from image time series. A brute-force search for the best alignment usually produces good results with proper cost functions, but becomes computationally expensive if the whole search space is explored. Hill climbing optimizations seek local optima. Particle filtering avoids local solutions by introducing randomness and sequentially updating the posterior distribution representing probable solutions. Thus, it can be more robust for the registration of image time series. We show promising preliminary results on dendrite image time series. © 2013 IEEE.