An ImageJ-based tool for three-dimensional registration between different types of microscopic images

ImageJ's macros for 3D registration and 3D image reconstruction are included with their manuals.</p

Histogram equalized 2D sample images from our image dataset.

<p>Sample images with (time point, z-slice) pairs at (A) (5,13), (B) (9,14), (c) (10,11), (D)(25,14), (E) (36,15), and (F) (83,18). Each image has dimension: 241×241 pixels and has voxel resolutions: x = y = 0.385 and z = 3 microns.</p

An Example of processing results for candidate regions and enhanced image.

<p>Two dimensional (2D) version of the original 3D (A) Input image, (B) Preprocessed image, (C) Candidate masks, (D) Candidate regions, and (E) Locally enhanced image (LEI).</p

Procedure for extraction of candidate nuclei centroids (Stage-1).

<p>Block diagram shows how we obtain candidate centroids systematically from locally enhanced image. (A) Locally enhanced image (LEI), (B) Candidate centroids. Spherical color regions indicate centers of local maxima regions.</p

Comparison of Sensitivity, Precision, and RMSE metrics for estimated nuclei (Variant-2).

<p>Performance of nuclei detection over 100 time points (i.e., 100 3D images) in terms of (A) Sensitivity, (B) Precision, and (C) Root Mean Square Error (RMSE). Blue and red graphs show the performance curves for our proposed and Bao’s method, respectively.</p

Evidence of Dynamic Pentagon−Heptagon Pairs in Single-Wall Carbon Nanotubes using Surface-Enhanced Raman Scattering

Surface-enhanced Raman scattering (SERS) was applied to detecting pentagon−heptagon pairs, the so-called Stone−Wales defect, in single-wall carbon nanotubes (SWCNTs). When a probing laser light was scanned over a SWCNT-dispersed silver surface, two distinct SERS spectra were obtained: (1) temporally stable spectra similar to that of resonance Raman spectra of bulk SWCNTs and (2) temporally fluctuating spectra with additional peaks which were not observed in the non-SERS spectra. The fluctuations in the SERS spectra are discussed in association with dynamic reconstruction of defective structures of SWCNTs (nonhexagonal arrangements of carbon atoms) in the vicinity of SERS-active sites under irradiation of the laser light

Results for nuclei extraction at various stages of centroid extraction.

<p>Number of estimated nuclei at various stages of the proposed method. Proposed method uses threshold parameters ( = 0.97) in the rough extraction stage (Stage-1), ( = 0.85) for the profile shape analysis (Stage-2), and (  = 15 pixels) for merging fragmented nuclei (Stage-3).</p

Results for centroid extraction at various stages of our method.

<p>(A, D) Stage-1 results of centroid extraction after local maxima searching for a sample image at t70, (B, E) Refined results of Stage-1 centroids after profile shape analysis using locally enhanced image (Stage-2), and (C, F) Refined results of Stage-2 centroids after combining fragmented nuclei (Stage-3). Top and bottom rows show the results for Variant-1 and Variant-2, respectively.</p

Results for centroid extraction by proposed method (Variant-2) for higher time–point images.

<p>(A–E) Preprocessed and manually thresholed 3D images (volume rendered) for time points t57, t70, t77, t85, and t97, respectively. (F–J) Corresponding results of centroid extraction. All individual centroids are represented by spherical regions using different colors.</p

Results of number of estimated nuclei by our method.

<p>Blue and red graphs show the plots of the estimated nuclei for (A) Variant-1 and (B) Variant-2 of our method and Bao’s method, respectively. The green graph shows manually identified GT centroids. These plots involve 100 3D images, captured at 100 discrete time points in the early developmental period of mouse–embryo.</p