<> "The repository administrator has not yet configured an RDF license."^^ . <> . . "A Software Ecosystem for Remote Analysis of Mass Spectrometry Imaging Data"^^ . "In many areas of biomedical research, images are crucial for scientific progress. Interactive\r\naccess to these images is essential, enhancing understanding and facilitating advancements,\r\nparticularly in fields like pathology, radiology, and cellular biology. As imaging techniques\r\ncontinue to advance, generating ever more detailed datasets, the amount of data to be stored\r\nand processed will continue to grow. Consequently, data and computationally intensive\r\nprocesses are being increasingly relocated to centralized resources with substantial storage\r\nand processing capabilities. However, large, multidimensional and multi-modal biomedical\r\nimages, such as those generated in experiments with mass spectrometry imaging, pose a\r\nmajor challenge for fast, comprehensive and interactive remote access. Processes as image\r\ndata exploration, image analysis, the development of new image analysis methods, and\r\ninterdisciplinary collaboration of domain experts can be hampered if data-intensive transfers\r\nto local systems are required, e.g. for processing of images with interactive applications\r\ndomain experts are familiar with. Current efforts to utilize remote resources focus on pro-\r\nviding integrated environments for remote development and applications for execution of\r\nreproducible image analysis, while lacking comprehensive interactive capabilities to work\r\nwith high-dimensional image data.\r\nThe first part of this work introduces advanced interactive access strategies for multi-\r\nmodal 2D/3D mass spectrometry imaging (MSI) datasets. Concepts for fast, memory-efficient\r\ninteractive access to imzML mass spectrometry imaging datasets are presented, which fa-\r\ncilitate advanced interactive workflows such as multi-modal image fusion and 3D image\r\nreconstruction. The effectiveness of the concepts are demonstrated within the context of the\r\nnovel and openly accessible desktop application called Mass spectrometry imaging Applications\r\nfor Interactive Analysis in MITK (M²aia). Furthermore, concepts for a programming language-\r\nindependent integration of third-party command-line applications via Docker (mitk-docker)\r\ninto the interactive framework of M²aia are presented. Finally, concepts for an optimized MSI\r\ndata access for deep learning are proposed and shown in combination with the data handling\r\nand processing capabilities of M²aia as part of a python package (pyM²aia).\r\nThe second part of this thesis proposes a versatile and efficient interactive remote working\r\nenvironment. It relies on interactive containerized applications that can be deployed with\r\nDocker and accessed using a web browser. The effectiveness of the concept is demonstrated\r\nby applying it to a diverse set of biomedical image processing applications, M²aia for MSI data,\r\nMITK for clinical images, ImageJ for microscopy images, QuPath for manual segmentation of\r\nhistology images, and ilastik for semi-automatic segmentation of a wide range of biomedical\r\nimaging modalities. Access to these remote-controlled applications facilitates a variety of\r\ninteractive tasks on remote image data such as image analysis, method development and\r\ncollaboration with experts.\r\nIn both parts of this work, diverse use-cases are elaborated to show the capabilities of the\r\nrespective concepts. Use-cases demonstrate the advanced interactive capabilities of M²aia\r\nwith respect to multi-modal image fusion and 3D image reconstructions. A comprehensive\r\nset of MSI-based deep learning use-cases is realized to showcase the data access capabilities\r\nof pyM²aia. Furthermore, the seamless integration of Docker-based applications into the\r\ninteractive environment of M²aia is demonstrated. Finally, capabilities of the interactive\r\nremote working environment are demonstrated.\r\nIn summary, this thesis introduces comprehensive concepts for processing and interactive\r\nanalysis of multi-modal 2D/3D mass spectrometry image data as well as additional concepts\r\nfor a general support of interactive remote working applying to a wide range of interactive\r\nbiomedical image processing tasks."^^ . "2025" . . . . . . . "Jonas"^^ . "Cordes"^^ . "Jonas Cordes"^^ . . . . . . "A Software Ecosystem for Remote Analysis of Mass Spectrometry Imaging Data (PDF)"^^ . . . "Dissertation.pdf"^^ . . . "A Software Ecosystem for Remote Analysis of Mass Spectrometry Imaging Data (Other)"^^ . . . . . . "lightbox.jpg"^^ . . . "A Software Ecosystem for Remote Analysis of Mass Spectrometry Imaging Data (Other)"^^ . . . . . . "preview.jpg"^^ . . . "A Software Ecosystem for Remote Analysis of Mass Spectrometry Imaging Data (Other)"^^ . . . . . . "medium.jpg"^^ . . . "A Software Ecosystem for Remote Analysis of Mass Spectrometry Imaging Data (Other)"^^ . . . . . . "small.jpg"^^ . . . "A Software Ecosystem for Remote Analysis of Mass Spectrometry Imaging Data (Other)"^^ . . . . . . "indexcodes.txt"^^ . . "HTML Summary of #36122 \n\nA Software Ecosystem for Remote Analysis of Mass Spectrometry Imaging Data\n\n" . "text/html" . . . "004 Informatik"@de . "004 Data processing Computer science"@en . .