12 papers · ranked by Valyu relevance
Weize Xu, Huaiyuan Cai, Qian Zhang, Zhengze Wang + 11 more
'Xiaofeng Wu' 'Chengwen Li' 'Chenghua Cui' 'Changzhi Liu' 'Jin He' 'Florian Mueller' 'Jinxia Dai' 'Chen Hao' 'Wei Ouyang' 'Gang Cao'] Imaging-based spatial-omics advances biomedical discoveries with subcellular resolution and high sensitivity, but accurately identifying signal spots from diverse images remains…
Felix Y. Zhou, Adam Norton-Steele, Lewis Marsh, Helen M. Byrne + 2 more
Cells are plastic, highly heterogeneous and change over time. High-content timelapse imaging promises to reveal dynamic cell behaviors, enabling more accurate identification of cell state and cell fate prediction for biological hypothesis generation and perturbation screens. To empower live-cell imaging based…
Xin Fan, Jun Li, Junan Yan, Liang Wang
Micturition serves an essential physiological function that allows the body to eliminate metabolic wastes and maintain water-electrolyte balance. The urine spot assay (VSA), as a simple and economical assay, has been widely used in the study of micturition behavior in rodents. However, the traditional VSA method relies…
Emmanuel Bouilhol, Anca F. Savulescu, Edgar Lefevre, Benjamin Dartigues + 2 more
'Benjamin Dartigues' 'Robyn Brackin' 'Macha Nikolski'] Detection of RNA spots in single-molecule fluorescence in-situ hybridization microscopy images remains a difficult task, especially when applied to large volumes of data. The variable intensity of RNA spots combined with the high noise level of the images often…
Jianxiang Dong, Zhaozheng Yin, Dale Kreitler, Herbert J. Bernstein + 2 more
'Jean Jakoncic' 'J. Hajdu'] Bragg Spot Finder (BSF) is a U-Net-based spotfinder with image preprocessing, a U-Net segmentation backbone, and post-processing that includes artifact removal and watershed segmentation. BSF is supported by the Bragg Spot Detection (BSD) benchmark image dataset containing more than 300…
Ella Bahry, Laura Breimann, Marwan Zouinkhi, Leo Epstein + 7 more
Fluorescent in-situ hybridization (FISH)-based methods extract spatially resolved genetic and epigenetic information from biological samples by detecting fluorescent spots in microscopy images, an often challenging task. We present Radial Symmetry-FISH (RS-FISH), an accurate, fast, and user-friendly software for spot…
Farzana Islam, Sumaya, Md Fahad Monir, Ashraful Islam
The FabricSpotDefect dataset is, to the best of our knowledge, the first dataset specifically designed to accurately challenge computer vision in detecting fabric spots. There are a total of 1014 raw images and manually annotated 3288 different categories of spots. This dataset expands to 2300 augmented images after…
Shengxian Yi, Zhongjiong Yang, Liqiang Zhou, Shaoxin Zou + 2 more
'Huangxin Xie' 'Carlo Alberto Avizzano'] In this paper, deep learning and image processing technologies are combined, and an automatic sampling robot is proposed that can completely replace the manual method in the three-dimensional space when used for the autonomous location of sampling points. It can also achieve…
Lingjiang Li, Maolin Li, Weijun Sun, Zhenni Li + 2 more
'Shah Nawaz Burokur'] Spot detection has attracted continuous attention for laser sensors with applications in communication, measurement, etc. The existing methods often directly perform binarization processing on the original spot image. They suffer from the interference of the background light. To reduce this kind…
Hongbo Yuan, Jiajun Zhu, Qifan Wang, Man Cheng + 1 more
The common method for evaluating the extent of grape disease is to classify the disease spots according to the area. The prerequisite for this operation is to accurately segment the disease spots. This paper presents an improved DeepLab v3+ deep learning network for the segmentation of grapevine leaf black rot spots.…
Tulio Fernandes De Almeida, Bruno Guedes Spinelli, Ramón Hypolito Lima, Maria Carolina Gonzalez + 1 more
Here we developed an open-source Python-based library called Python rodent Analysis and Tracking (PyRAT). Our library analyzes tracking data to classify distinct behaviors, estimate traveled distance, speed and area occupancy. To classify and cluster behaviors, we used two unsupervised algorithms: hierarchical…
Wei Liu, Bo Wang, Yuting Bai, Xiao Liang + 2 more
Spatial transcriptomics technologies enable the generation of gene expression profiles while preserving spatial context, providing the potential for in-depth understanding of spatial-specific tissue heterogeneity. Leveraging gene and spatial data effectively is fundamental to accurately identifying spatial domains in…