Sökning: "liver segmentation"

Visar resultat 1 - 5 av 12 uppsatser innehållade orden liver segmentation.

1. 1. Exploring adaptation of self-supervised representation learning to histopathology images for liver cancer detection

   Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Författare :Markus Jonsson; [2024]
   Nyckelord :Self-supervised learning; Representation learning; Computer vision;

   Sammanfattning : This thesis explores adapting self-supervised representation learning to visual domains beyond natural scenes, focusing on medical imaging. The research addresses the central question: "How can self-supervised representation learning be specifically adapted for detecting liver cancer in histopathology images?" The study utilizes the PAIP 2019 dataset for liver cancer segmentation and employs a self-supervised approach based on the VICReg method. LÄS MER

3. 2. Self-learning for 3D segmentation of medical images from single and few-slice annotation

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Côme Lassarat; [2023]
   Nyckelord :Self-supervised Learning; Segmentation; Medical images; Självövervakad inlärning; segmentering; medicinska bilder;

   Sammanfattning : 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. LÄS MER

4. 3. Uncertainty Estimation in Volumetric Image Segmentation

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Donggyun Park; [2023]
   Nyckelord :Uncertainty Estimation; Uncertainty Quantification UQ ; Volumetric Image Segmentation; 3D U-Net; test-time data augmentation; Deep ensemble;

   Sammanfattning : 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. LÄS MER

5. 4. Development and evaluation of an inter-subject image registration method for body composition analysis for three slice CT images

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Hugo Dahlberg; [2022]
   Nyckelord :Medical imaging; Image registration; SCAPIS;

   Sammanfattning : Over 30 000 liver, abdomen, and thigh slices have been acquired by computed tomography for the SCAPIS and IGT study. To utilise the full potential of the large cohort and enable statistical pixel-wise body composition analysis and visualisation of associations with other biomarkers, a point-to-point correspondence between the scans is needed. LÄS MER

7. 5. Feasibility of Dynamic SPECT-Renography with Automated Evaluation Using a Deep Neural Network

   Master-uppsats, Lunds universitet/Sjukhusfysikerutbildningen

   Författare :Viktor Rogowski; [2021]
   Nyckelord :Medicine and Health Sciences;

   Sammanfattning : Introduction: Renography is a standard diagnostic examination that evaluates renal function, renal pelvic dilatation and urinary obstruction. Renography is performed by injecting a radiopharmaceutical (predominately 99mTc-MAG3) and using gamma camera to image the biodistribution in a dynamic sequence. LÄS MER