Sökning: "automatic segmentation"

Visar resultat 1 - 5 av 86 avhandlingar innehållade orden automatic segmentation.

1. 1. Automatic Virus Identification using TEM : Image Segmentation and Texture Analysis

   Författare :Gustaf Kylberg; Ida-Maria Sintorn; Gunilla Borgefors; Walter Kropatsch; Uppsala universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; image analysis; image processing; virus identification; transmission electron microscopy; texture analysis; texture descriptors; Computerized Image Processing; Datoriserad bildbehandling;

   Sammanfattning : Viruses and their morphology have been detected and studied with electron microscopy (EM) since the end of the 1930s. The technique has been vital for the discovery of new viruses and in establishing the virus taxonomy. Today, electron microscopy is an important technique in clinical diagnostics. LÄS MER

3. 2. Segmentation of Laser Range Radar Images using Hidden Markov Field Models

   Författare :Predrag Pucar; Linköpings universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Segmentation; Images; Model based stochastic techniques; Image processing; Demanding algorithms; Hidden Markov model; Estimation; Automatic control; Reglerteknik;

   Sammanfattning : Segmentation of images in the context of model based stochastic techniques is connected with high, very often unpracticle computational complexity. The objective with this thesis is to take the models used in model based image processing, simplify and use them in suboptimal, but not computationally demanding algorithms. LÄS MER

4. 3. Resource efficient automatic segmentation of medical images

   Författare :Minh Hoang Vu; Tommy Löfstedt; Tufve Nyholm; Anders Garpebring; Joakim Jonsson; Örjan Smedby; Umeå universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; radiotherapy; medical imaging; deep learning; convolutional neural network; generative adversarial network; data augmentation; semantic segmentation; classification; activation map compression; radiofysik; radiation physics;

   Sammanfattning : Cancer is one of the leading causes of death worldwide. In 2020, there were around 10 million cancer deaths and nearly 20 million new cancer cases in the world. Radiation therapy is essential in cancer treatments because half of the cancer patients receive radiation therapy at some point. LÄS MER

5. 4. Fast Methods for Vascular Segmentation Based on Approximate Skeleton Detection

   Författare :Kristína Lidayová; Hans Frimmel; Ewert Bengtsson; Örjan Smedby; Alejandro F. Frangi; Uppsala universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; medical image analysis; automatic skeleton extraction; vascular segmentation; coverage segmentation; convolutional neural network classifier; CT angiography; Computerized Image Processing; Datoriserad bildbehandling;

   Sammanfattning : Modern medical imaging techniques have revolutionized health care over the last decades, providing clinicians with high-resolution 3D images of the inside of the patient's body without the need for invasive procedures. Detailed images of the vascular anatomy can be captured by angiography, providing a valuable source of information when deciding whether a vascular intervention is needed, for planning treatment, and for analyzing the success of therapy. LÄS MER

7. 5. Towards Fully Automatic Optimal Shape Modeling

   Författare :Johan Karlsson; Matematik LTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Parameterization Invariance; Benchmarking; Interpretation; Segmentation; Alignment; Shape Modeling; MDL;

   Sammanfattning : Shape models and the automatic building of such models have proven over the last decades to be powerful tools in image segmentation and analysis. This thesis makes contributions to this field. The segmentation algorithm typically uses an objective function summing up contributions from each sample point. LÄS MER