The Multiscale Morphology Filter: Identifying and Extracting Spatial Patterns in the Galaxy Distribution

We present here a new method, MMF, for automatically segmenting cosmic structure into its basic components: clusters, filaments, and walls. Importantly, the segmentation is scale independent, so all structures are identified without prejudice as to their size or shape. The method is ideally suited for extracting catalogues of clusters, walls, and filaments from samples of galaxies in redshift surveys or from particles in cosmological N-body simulations: it makes no prior assumptions about the scale or shape of the structures.}Comment: Replacement with higher resolution figures. 28 pages, 17 figures. For Full Resolution Version see: http://www.astro.rug.nl/~weygaert/tim1publication/miguelmmf.pd

IR Colors and Sizes of Faint Galaxies

We present J and Ks band galaxy counts down to J=24 and Ks=22.5 obtained with the new infrared imager/spectrometer, SOFI, at the ESO New Technology Telescope. The co-addition of short, dithered, images led to a total exposure time of 256 and 624 minutes respectively, over an area of $\sim20$ arcmin$^2$ centered on the NTT Deep Field. The total number of sources with S/N$>5$ is 1569 in the J sample and 1025 in the Ks-selected sample. These are the largest samples currently available at these depths. A d$logN$/d$m$ relation with slope of $\sim0.36$ in J and $\sim0.38$ in Ks is found with no evident sign of a decline at the magnitude limit. The observed surface density of ``small'' sources is much lower than ``large'' ones at bright magnitudes and rises more steeply than the large sources to fainter magnitudes. Fainter than $J\sim22.5$ and Ks$\sim21.5$, small sources dominate the number counts. Galaxies get redder in J-K down to J$\sim20$ and Ks$\sim19$. At fainter magnitudes, the median color becomes bluer with an accompanying increase in the compactness of the galaxies. We show that the blue, small sources which dominate the faint IR counts are not compatible with a high redshift ($z>1$) population. On the contrary, the observed color and compactness trends, together with the absence of a turnover at faint magnitudes and the dominance of small sources, can be naturally explained by an increasing contribution of sub-$L^*$ galaxies when going to fainter apparent magnitudes. Such evidence strongly supports the existence of a steeply rising ($\alpha\ll-1$) faint end of the local infrared luminosity function of galaxies - at least for luminosities $L<0.01L^*$.Comment: Accepted for publication on A&A; 15 pages, 13 figure

Automated Segmentation of Cells with IHC Membrane Staining

This study presents a fully automated membrane segmentation technique for immunohistochemical tissue images with membrane staining, which is a critical task in computerized immunohistochemistry (IHC). Membrane segmentation is particularly tricky in immunohistochemical tissue images because the cellular membranes are visible only in the stained tracts of the cell, while the unstained tracts are not visible. Our automated method provides accurate segmentation of the cellular membranes in the stained tracts and reconstructs the approximate location of the unstained tracts using nuclear membranes as a spatial reference. Accurate cell-by-cell membrane segmentation allows per cell morphological analysis and quantification of the target membrane proteins that is fundamental in several medical applications such as cancer characterization and classification, personalized therapy design, and for any other applications requiring cell morphology characterization. Experimental results on real datasets from different anatomical locations demonstrate the wide applicability and high accuracy of our approach in the context of IHC analysi

Structure-dependent amplification for denoising and background correction in Fourier ptychographic microscopy

Fourier Ptychographic Microscopy (FPM) allows high resolution imaging using iterative phase retrieval to recover an estimate of the complex object from a series of images captured under oblique illumination. FPM is particularly sensitive to noise and uncorrected background signals as it relies on combining information from brightfield and noisy darkfield (DF) images. In this article we consider the impact of different noise sources in FPM and show that inadequate removal of the DF background signal and associated noise are the predominant cause of artefacts in reconstructed images. We propose a simple solution to FPM background correction and denoising that outperforms existing methods in terms of image quality, speed and simplicity, whilst maintaining high spatial resolution and sharpness of the reconstructed image. Our method takes advantage of the data redundancy in real space within the acquired dataset to boost the signal-to-background ratio in the captured DF images, before optimally suppressing background signal. By incorporating differentially denoised images within the classic FPM iterative phase retrieval algorithm, we show that it is possible to achieve efficient removal of background artefacts without suppression of high frequency information. The method is tested using simulated data and experimental images of thin blood films, bone marrow and liver tissue sections. Our approach is non-parametric, requires no prior knowledge of the noise distribution and can be directly applied to other hardware platforms and reconstruction algorithms making it widely applicable in FPM