Essays about: "Ground-truth"

Showing result 11 - 15 of 245 essays containing the word Ground-truth.

  1. 11. Automated Interpretation of Lung Ultrasound for COVID-19 and Tuberculosis diagnosis

    University essay from Lunds universitet/Matematik LTH

    Author : Chloé Soormally; [2023]
    Keywords : Tuberculosis; COVID-19; Lung Ultrasound; Computer-aided detection CAD ; Deep learning; Technology and Engineering;

    Abstract : BACKGROUND. Early and accurate detection of infectious respiratory diseases like COVID-19 and tuberculosis (TB) plays a crucial role in effective management and the reduction of preventable mortality. READ MORE

  3. 12. Unsupervised Clustering of Behavior Data From a Parking Application : A Heuristic and Deep Learning Approach

    University essay from Umeå universitet/Institutionen för matematik och matematisk statistik

    Author : Edvard Magnell; Joakim Nordling; [2023]
    Keywords : ML; Machine learning; clustering; unsupervised learning; deep learning; autoencoder; AI; artificial intelligence;

    Abstract : This report aims to present a project in the field of unsupervised clustering on human behavior in a parking application. With increasing opportunities to collect and store data, the demands to utilize the data in meaningful ways also increase. READ MORE

  4. 13. Using Generative Adversarial Networks for H&E-to-HER2 Stain Translation in Digital Pathology Images

    University essay from Linköpings universitet/Institutionen för medicinsk teknik

    Author : William Tirmén; [2023]
    Keywords : Machine learning; Artificial intelligence; Digital pathology; Image processing; Generative adversarial networks; Image-to-image translation;

    Abstract : In digital pathology, hematoxylin & eosin (H&E) is a routine stain which is performed on most clinical cases and it often provides clinicians with sufficient information for diagnosis. However, when making decisions on how to guide breast cancer treatment, immunohistochemical staining of human epidermal growth factor 2 (HER2 staining) is also needed. READ MORE

  5. 14. Physiology-Guided Machine Learning for Improved Reliability of Non-Invasive Assessment of Pulmonary Hypertension

    University essay from Linköpings universitet/Avdelningen för medicinsk teknik

    Author : Frida Hermansson; [2023]
    Keywords : Pulmonary Hypertension; pulmonary hypertension; improving; physiological-guided; machine learning; neural networks; NN; artificial neural networks; non-invasive; PH; tricuspid regurgitation; peak tricuspid regurgitation velocity; tricuspid regurgitation velocity; right ventricular systolic pressure; VGG16; Unet; TR-CNN; CNN; pulmonell hypertension; förbättra; fysiologisk-guidning; neurala nätverk; trikuspidal regurgitation; maximal trikuspidal regurgitation; icke-invasivt;

    Abstract : Diagnosing pulmonary hypertension (PH) with right heart catheterization (RHC) is associated with a risk for complications and high expenses, leading to late diagnoses [1]. Transthoracic echocardiography can be used to assess non-invasive indicators for PH such as right ventricular systolic pressure (RVSP), which can be estimated by combining the peak tricuspid regurgitation velocity (TRV) with the estimated right arterial pressure (RAP). READ MORE

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

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

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

    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