Sökning: "Tumor Segmentation"

Visar resultat 1 - 5 av 10 avhandlingar innehållade orden Tumor Segmentation.

  1. 1. Advanced Machine Learning Methods for Oncological Image Analysis

    Författare :Mehdi Astaraki; Chunliang Wang; Örjan Smedby; Iuliana Toma-Dasu; Bjoern Menze; KTH; Karolinska Institutet; Karolinska Institutet; []
    Nyckelord :ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Medical Image Analysis; Machine Learning; Deep Learning; Survival Analysis; Early Response Assessment; Tumor Classification; Tumor Segmentation; Medicinsk teknologi; Medical Technology;

    Sammanfattning : Cancer is a major public health problem, accounting for an estimated 10 million deaths worldwide in 2020 alone. Rapid advances in the field of image acquisition and hardware development over the past three decades have resulted in the development of modern medical imaging modalities that can capture high-resolution anatomical, physiological, functional, and metabolic quantitative information from cancerous organs. LÄS MER

  2. 2. Quantitative methods for tumor imaging with dynamic PET

    Författare :Ida Häggström; Anne Larsson; Mikael Karlsson; Lennart Johansson; Jens Sörensen; Magnus Dahlbom; Umeå universitet; []
    Nyckelord :ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; TEKNIK OCH TEKNOLOGIER; NATURAL SCIENCES; ENGINEERING AND TECHNOLOGY; Dynamic positron emission tomography; PET; tumor imaging; compartment modeling; Monte Carlo; radiofysik; radiation physics;

    Sammanfattning : There is always a need and drive to improve modern cancer care. Dynamic positron emission tomography (PET) offers the advantage of in vivo functional imaging, combined with the ability to follow the physiological processes over time. LÄS MER

  3. 3. Development of a Whole Body Atlas for Radiation Therapy Planning and Treatment Optimization

    Författare :Sharif Qatarneh; Anders Brahme; Bengt Lind; Anders Ahnesjö; Stockholms universitet; []
    Nyckelord :3D whole body atlas; lymph node topography; matching transformation; radiation therapy planning; radiobiological optimization; segmentation; target volume definition; medicinsk strålningsfysik; Medical Radiation Physics;

    Sammanfattning : The main objective of radiation therapy is to obtain the highest possible probability of tumor cure while minimizing adverse reactions in healthy tissues. A crucial step in the treatment process is to determine the location and extent of the primary tumor and its loco regional lymphatic spread in relation to adjacent radiosensitive anatomical structures and organs at risk. LÄS MER

  4. 4. Artificial Intelligence-based Assessment of Prostate Cancer Metastases in PET/CT

    Författare :Sarah Lindgren Belal; Malmö Nuklearmedicin; []
    Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Artificial intelligence AI ; Convolutional neural networks CNN ; PET CT; Prostate cancer; Automated; Tumor burden; Bone metastases; Lymph node metastases;

    Sammanfattning : Background: Quantification of tumor burden from bone scan in the form of automated Bone Scan Index (aBSI) has been validated as an imaging biomarker for patients with prostate cancer. Positron emission tomography combined with computed tomography (PET/CT) is more sensitive and accurate compared to conventional imaging such as bone scan. LÄS MER

  5. 5. A path along deep learning for medical image analysis : With focus on burn wounds and brain tumors

    Författare :Marco Domenico Cirillo; Anders Eklund; Veronika Cheplygina; Linköpings universitet; []
    Nyckelord :ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Deep learning; Medical image analysis; Burn wounds; Brain tumors; Image classification; Image segmentation; Image augmentation; CNNs; GANs;

    Sammanfattning : The number of medical images that clinicians need to review on a daily basis has increased dramatically during the last decades. Since the number of clinicians has not increased as much, it is necessary to develop tools which can help doctors to work more efficiently. LÄS MER