相关论文: Three-dimensional imaging of biological cells usin…
This tutorial covers biomedical image reconstruction, from the foundational concepts of system modeling and direct reconstruction to modern sparsity and learning-based approaches. Imaging is a critical tool in biological research and…
Advances in fluorescence microscopy enable acquisition of 3D image volumes with better image quality and deeper penetration into tissue. Segmentation is a required step to characterize and analyze biological structures in the images and…
Results: We present an application that enables the quantitative analysis of multichannel 5-D (x, y, z, t, channel) and large montage confocal fluorescence microscopy images. The image sequences show stem cells together with blood vessels,…
We describe a 3D percolation-type approach to modeling of the processes of aging and certain other properties of tissues analyzed as systems consisting of interacting cells. Lattice sites are designated as regular (healthy) cells, senescent…
Fluorescent imaging plays a critical role in a myriad of scientific endeavors, particularly in the biological sciences. Three-dimensional imaging of fluorescent intensity often requires serial data acquisition, that is voxel-by-voxel…
Structured illumination microscopy (SIM) has emerged as an essential technique for 3D and live-cell super-resolution imaging. However, to date, there has not been a dedicated workshop or journal issue covering the various aspects of SIM,…
Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge…
Current high-resolution imaging techniques require an intact sample that preserves spatial relationships. We here present a novel approach, "puzzle imaging," that allows imaging a spatially scrambled sample. This technique takes many…
We present a novel method for 3D surface reconstruction from multiple images where only a part of the object of interest is captured. Our approach builds on two recent developments: surface reconstruction using neural radiance fields for…
Diffusion models have recently emerged as a powerful technique in image generation, especially for image super-resolution tasks. While 2D diffusion models significantly enhance the resolution of individual images, existing diffusion-based…
Cell image classification methods are currently being used in numerous applications in cell biology and medicine. Applications include understanding the effects of genes and drugs in screening experiments, understanding the role and…
3D cell segmentation methods are often hindered by \emph{oversegmentation}, where a single cell is incorrectly split into multiple fragments. This degrades the final segmentation quality and is notoriously difficult to resolve, as…
Video-rate super-resolution imaging through biological tissue can visualize and track biomolecule interplays and transportations inside cellular organisms. Structured illumination microscopy allows for wide-field super resolution…
We propose a new objective numerical figure of merit to aid in the evaluation and comparison of tissue-selective images generated from dual-energy radiography systems. A metric is developed through identification of the requirements of a…
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…
Volumetric cell segmentation in fluorescence microscopy images is important to study a wide variety of cellular processes. Applications range from the analysis of cancer cells to behavioral studies of cells in the embryonic stage. Like in…
In this work, we study the perception problem for sampled surfaces (possibly with boundary) using tools from computational topology, specifically, how to identify their underlying topology starting from point-cloud samples in space, such as…
With the thriving of deep learning, 3D Convolutional Neural Networks have become a popular choice in volumetric image analysis due to their impressive 3D contexts mining ability. However, the 3D convolutional kernels will introduce a…
Subwavelength imaging by microsphere lenses is a promising label-free super-resolution imaging technique. There is a growing interest to use live cells to replace the widely used non-biological microsphere lenses. In this work, we…
3D beamforming is a promising approach for interference coordination in cellular networks which brings significant improvements in comparison with conventional 2D beamforming techniques. This paper investigates the problem of joint…