Sökning: "X-ray detection"

Visar resultat 1 - 5 av 62 uppsatser innehållade orden X-ray detection.

1. 1. Developing a highly accurate, locally interpretable neural network for medical image analysis

   Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Rony David Ventura Caballero; [2023]
   Nyckelord :XAI; Interpretability; Computer vision; Pediatric pneumonia; Chest radiograph;

   Sammanfattning : Background Machine learning techniques, such as convolutional networks, have shown promise in medical image analysis, including the detection of pediatric pneumonia. However, the interpretability of these models is often lacking, compromising their trustworthiness and acceptance in medical applications. LÄS MER

3. 2. Barium in the O horizon of soils near Sundsvall, northern Sweden : From local minerals or from anthropogenic emissions?

   Kandidat-uppsats, Umeå universitet/Institutionen för ekologi, miljö och geovetenskap

   Författare :Mattias Åsberg Gencturk; [2023]
   Nyckelord :Barium; soil; organic horizon;

   Sammanfattning : Concentrations of potentially toxic metals in surface soils are important to investigate before building new residential areas. Prior to development of a residential area in Sundsvall, northern Sweden, it was observed that barium (Ba) concentrations in the soil at the site exceeded the guideline value of 200 mg kg-1 outlined by the Swedish Environmental Protection Agency. LÄS MER

4. 3. The effect of model calibration on noisy label detection

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

   Författare :Max Joel Söderberg; [2023]
   Nyckelord :Area Under the Margin; Calibration; Image classification; Label smoothing; Noisy labels; Overconfidence; Area under marginalen; Kalibrering; Bildklassificering; Etikettutjämning; Brusiga etiketter; Övertro;

   Sammanfattning : The advances in deep neural networks in recent years have opened up the possibility of using image classification as a valuable tool in various areas, such as medical diagnosis from x-ray images. However, training deep neural networks requires large amounts of annotated data which has to be labelled manually, by a person. LÄS MER

5. 4. Study of surfactant-preservative and protein-preservative interactions in multi-dose injectable formulation

   Master-uppsats, Lunds universitet/Livsmedelsteknik och nutrition (master)

   Författare :Javier Lagares Martín; [2023]
   Nyckelord :Phenol; polysorbate 80; cloud point; somatropin; aggregation; titration; light scattering; salt; surfactant; preservative; protein; tonicity adjusting agents; multi-dose injectable formulation; pharmaceutical technology; Technology and Engineering;

   Sammanfattning : Multidose injectable formulations require a preservative such as phenol to ensure sterility and protection against microbial contamination during clinical use. However, it is known that the interaction between these components and non-ionic surfactants such as polysorbate 80, also found in this type of formulations, present incompatibilities, which can lead to decreases in the efficacy of the product. LÄS MER

7. 5. Segmentation of x-ray images using deep learning trained on synthetic data

   Master-uppsats, KTH/Fysik

   Författare :Marcus Larsson; [2023]
   Nyckelord :Radiography; Deep Learning; Synthetic Data; Segmentation; Röntgen; Djupinlärning; Syntetisk Data; Segmentering;

   Sammanfattning : Radiograph examinations play a critical role in various applications such as the detection of bone pathologies and lung cancer, despite the challenge of false negatives. The integration of Artificial Intelligence (AI) holds promise in enhancing image quality and assisting radiologists in their diagnostic processes. LÄS MER