Sznitman R Lucchi A Cantoni M Knott G Fua P 2013 Scanning Electron Microscopy (SEM) is an invaluable tool for biologists and neuroscientists to study brain structure at the intracellular level. While able to image tissue samples with up to 5 nm isotropic resolution, image acquisition is prohibitively slow and limits the size of processed samples. In this work, we propose a novel approach to speeding up imaging when looking for specific structures. Unlike earlier methods, we explicitly balance the conflicting requirements of spending enough time scanning potential regions of interest to ensure that all targets are found while not wasting time on unpromising regions. This is achieved by using a Markov Random Field to model target locations and optimizing scanning locations by using a Branch-and-Bound strategy. We show that our approach significantly outperforms state-of-the-art methods to locate mitochondria in brain tissue. application/pdf https://sonar.ch/global/documents/204407 eng info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-642-40760-4_52 info:eu-repo/semantics/altIdentifier/pmid/24505788 info:eu-repo/semantics/openAccess Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. - 2013 Algorithms Brain Humans Image Enhancement Image Interpretation, Computer-Assisted Microscopy, Electron, Scanning Mitochondria Pattern Recognition, Automated Reproducibility of Results Sensitivity and Specificity Flash scanning electron microscopy. http://purl.org/coar/resource_type/c_6501