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FTIR spectroscopy is an emerging technology with high potential for cancer diagnosis but with particular physical
phenomena that require special processing. Little work has been done in the field with the aim of registering
hyperspectral Fourier-Transform Infrared (FTIR) spectroscopic images and Hematoxilin and Eosin (HE) stained
histological images of contiguous slices of tissue. This registration is necessary to transfer the location of relevant
structures that the pathologist may identify in the gold standard HE images. A two-step registration framework
is presented where a representative gray image extracted from the FTIR hypercube is used as an input. This
representative image, which must have a spatial contrast as similar as possible to a gray image obtained from
the HE image, is calculated through the spectrum variation in the fingerprint region. In the first step of the
registration algorithm a similarity transformation is estimated from interest points, which are automatically
detected by the popular SURF algorithm. In the second stage, a variational registration framework defined in
the frequency domain compensates for local anatomical variations between both images. After a proper tuning
of some parameters the proposed registration framework works in an automated way. The method was tested on
7 samples of colon tissue in different stages of cancer. Very promising qualitative and quantitative results were
obtained (a mean correlation ratio of 92.16% with a standard deviation of 3.10%).
Francisco Peñaranda,Valery Naranjo,Rafaél Verdú,Gavin R. Lloyd,Jayakrupakar Nallala, andNick Stone
"A two-step framework for the registration of HE stained and FTIR images", Proc. SPIE 9703, Optical Biopsy XIV: Toward Real-Time Spectroscopic Imaging and Diagnosis, 970305 (7 March 2016); https://doi.org/10.1117/12.2208869
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Francisco Peñaranda, Valery Naranjo, Rafaél Verdú, Gavin R. Lloyd, Jayakrupakar Nallala, Nick Stone, "A two-step framework for the registration of HE stained and FTIR images," Proc. SPIE 9703, Optical Biopsy XIV: Toward Real-Time Spectroscopic Imaging and Diagnosis, 970305 (7 March 2016); https://doi.org/10.1117/12.2208869