7,089 research outputs found
Coercive Region-level Registration for Multi-modal Images
We propose a coercive approach to simultaneously register and segment
multi-modal images which share similar spatial structure. Registration is done
at the region level to facilitate data fusion while avoiding the need for
interpolation. The algorithm performs alternating minimization of an objective
function informed by statistical models for pixel values in different
modalities. Hypothesis tests are developed to determine whether to refine
segmentations by splitting regions. We demonstrate that our approach has
significantly better performance than the state-of-the-art registration and
segmentation methods on microscopy images.Comment: This work has been accepted to International Conference on Image
Processing (ICIP) 201
Automatic Segmentation of Fluorescence Lifetime Microscopy Images of Cells Using Multi-Resolution Community Detection
We have developed an automatic method for segmenting fluorescence lifetime
(FLT) imaging microscopy (FLIM) images of cells inspired by a multi-resolution
community detection (MCD) based network segmentation method. The image
processing problem is framed as identifying segments with respective average
FLTs against a background in FLIM images. The proposed method segments a FLIM
image for a given resolution of the network composed using image pixels as the
nodes and similarity between the pixels as the edges. In the resulting
segmentation, low network resolution leads to larger segments and high network
resolution leads to smaller segments. Further, the mean-square error (MSE) in
estimating the FLT segments in a FLIM image using the proposed method was found
to be consistently decreasing with increasing resolution of the corresponding
network. The proposed MCD method outperformed a popular spectral clustering
based method in performing FLIM image segmentation. The spectral segmentation
method introduced noisy segments in its output at high resolution. It was
unable to offer a consistent decrease in MSE with increasing resolution.Comment: 21 pages, 6 figure
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