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Showing result 16 - 20 of 228 essays matching the above criteria.
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16. Comparative Analysis of Transformer and CNN Based Models for 2D Brain Tumor Segmentation
University essay from Linköpings universitet/Institutionen för medicinsk teknikAbstract : A brain tumor is an abnormal growth of cells within the brain, which can be categorized into primary and secondary tumor types. The most common type of primary tumors in adults are gliomas, which can be further classified into high-grade gliomas (HGGs) and low-grade gliomas (LGGs). READ MORE
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17. Optic nerve sheath diameter semantic segmentation and feature extraction
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Traumatic brain injury (TBI) affects millions of people worldwide, leading to significant mortality and disability rates. Elevated intracranial pressure (ICP) resulting from TBI can cause severe complications and requires early detection to improve patient outcomes. READ MORE
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18. Generating Synthetic Training Data with Stable Diffusion
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : The usage of image classification in various industries has grown significantly in recentyears. There are however challenges concerning the data used to train such models. Inmany cases the data used in training is often difficult and expensive to obtain. Furthermore,dealing with image data may come with additional problems such as privacy concerns. READ MORE
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19. Self-supervised pre-training of an attention-based model for 3D medical image segmentation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Accurate segmentation of anatomical structures is crucial for radiation therapy in cancer treatment. Deep learning methods have been demonstrated effective for segmentation of 3D medical images, establishing the current standard. However, they require large amounts of labelled data and suffer from reduced performance on domain shift. READ MORE
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20. Segmentation of x-ray images using deep learning trained on synthetic data
University essay from KTH/FysikAbstract : Radiograph examinations play a critical role in various applications such as the detection of bone pathologies and lung cancer, despite the challenge of false negatives. The integration of Artificial Intelligence (AI) holds promise in enhancing image quality and assisting radiologists in their diagnostic processes. READ MORE