Essays about: "Medicinsk bildsegmentering"
Showing result 1 - 5 of 10 essays containing the words Medicinsk bildsegmentering.
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1. Self-learning for 3D segmentation of medical images from single and few-slice annotation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Training deep-learning networks to segment a particular region of interest (ROI) in 3D medical acquisitions (also called volumes) usually requires annotating a lot of data upstream because of the predominant fully supervised nature of the existing stateof-the-art models. To alleviate this annotation burden for medical experts and the associated cost, leveraging self-learning models, whose strength lies in their ability to be trained with unlabeled data, is a natural and straightforward approach. READ MORE
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2. 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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3. 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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4. Uncertainty Estimation in Volumetric Image Segmentation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The performance of deep neural networks and estimations of their robustness has been rapidly developed. In contrast, despite the broad usage of deep convolutional neural networks (CNNs)[1] for medical image segmentation, research on their uncertainty estimations is being far less conducted. READ MORE
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5. Dealing With Speckle Noise in Deep Neural Network Segmentation of Medical Ultrasound Images
University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)Abstract : Segmentation of ultrasonic images is a common task in healthcare that requires time and attention from healthcare professionals. Automation of medical image segmentation using deep learning solutions is fast growing field and has been shown to be capable of near human performance. READ MORE
