Bridging the Gap Between Computational Efficiency and Segmentation Fidelity in Object-Based Image Analysis by Fernanda Pereira Leite Aguiar, Irenilza de Alencar Nääs, Marcelo Tsuguio Okano

“…This study presents a scalable and efficient framework designed to advance machine learning applications in complex image analysis tasks by incorporating methodologies for image quantization and automated segmentation.…”
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Deep learning driven interpretable and informed decision making model for brain tumour prediction using explainable AI by Khan Muhammad Adnan, Taher M. Ghazal, Muhammad Saleem, Muhammad Sajid Farooq, Chan Yeob Yeun, Munir Ahmad, Sang-Woong Lee

“…The advent of deep learning has made it a powerful tool for complex image analysis tasks, such as detecting brain Tumours, by learning advanced patterns from images. …”
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Transfer of Periodic Phenomena in Multiphase Capillary Flows to a Quasi-Stationary Observation Using U-Net by Bastian Oldach, Philipp Wintermeyer, Norbert Kockmann

“…X-ray-based Computer Tomography adds a third dimension to images, which results in more information, but ultimately, also in more complex image analysis. In this work, we present the application of the U-Net neural network to extract certain states during droplet formation in a capillary, which forms a constantly repeated process that is captured on tens of thousands of CT images. …”
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Cardiac computed tomography: Current practice, guidelines, applications, and prospects by Yu-Tai Shih, Jia-Hao Zhou, Jong-Kai Hsiao

“…Furthermore, it highlights the integration of machine learning to automate complex imaging analysis and photon-counting CT, which promises higher resolution and further dose reduction. …”
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