Sökning: "Biomedical imaging"

Visar resultat 1 - 5 av 45 uppsatser innehållade orden Biomedical imaging.

1. 1. Prediction of the gain in classification performance from combining multiple imaging modalities

   Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Roman Denkin; [2023]
   Nyckelord :;

   Sammanfattning : In this work, we investigate the relationship between different image modalities and classification performance, aiming to predict the potential gain in classification accuracy when combining multiple modalities. We analyze mathematical and statistical measures and develop novel reconstruction measures (RMSE and RSSIM) to assess information distribution between different image modalities. LÄS MER

3. 2. Applicerbarhet av Scaled Reassigned Spectrogram for Transient Signals (ReSTS) på ultraljudssignaler från biologisk vävnad

   Kandidat-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknik

   Författare :Sara Florentsson; Anna Hollsten; [2022]
   Nyckelord :Ultrasound; resolution; biological tissue; signal processing; Technology and Engineering;

   Sammanfattning : The possibility of being able to examine the inside of the human body is the foundation of today’s medical diagnostics. This can be done through different imaging systems, where ultrasound is one of the most important imaging methods used. LÄS MER

4. 3. Continual Learning and Biomedical Image Data : Attempting to sequentially learn medical imaging datasets using continual learning approaches

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

   Författare :Davit Soselia; [2022]
   Nyckelord :Deep Learning; Continual Learning; Catastrophic Forgetting; Biomedical Image Classification; Djup inlärning; kontinuerligt lärande; katastrofal glömska; biomedicinsk bildklassificering;

   Sammanfattning : While deep learning has proved to be useful in a large variety of tasks, a limitation remains of needing all classes and samples to be present at the training stage in supervised problems. This is a major issue in the field of biomedical imaging since keeping samples in the training sets consistently is often a liability. LÄS MER

5. 4. Mikrofluidikchipp för exponering av biologiska partiklar för varierande molekylära stimuli

   Kandidat-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknik

   Författare :Ebba Fritzell; Annie Mentzer; [2022]
   Nyckelord :Technology and Engineering;

   Sammanfattning : Easy exposure of biological particles for molecular stimuli is of interest when examining the effects of antibiotics on different bacteria or to perform toxicity analysis for biophysical studies of vesicles. Such experiments require advanced equipment that can only be found in laboratories and are vastly time-consuming. LÄS MER

7. 5. Medical image captioning based on Deep Architectures

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

   Författare :Georgios Moschovis; [2022]
   Nyckelord :Artificial Neural Networks; Deep Learning; Speech and language technology; Natural Language Processing NLP ; Deep networks; Generative deep networks; Convolutional neural networks CNN ; Text generation; Information retrieval; Diagnostic captioning; Image captioning; concept prediction; classification; image encoders; transformers; Encoder-Decoder architecture; abstractive summarization; Neurala nätverk; Djup inlärning; Tal-och språkteknologi; naturlig språkbehandling; djup neurala nätverk; generativa djupa nätverk; konvolutionella neurala nätverk; Textgenerering; Informationssökning; Diagnostisk textning; Bildtextning; konceptförutsägelse; klassificering; bildkodare; transformatorer; kodaravkodararkitektur; abstrakt sammanfattning;

   Sammanfattning : Diagnostic Captioning is described as “the automatic generation of a diagnostic text from a set of medical images of a patient collected during an examination” [59] and it can assist inexperienced doctors and radiologists to reduce clinical errors or help experienced professionals increase their productivity. In this context, tools that would help medical doctors produce higher quality reports in less time could be of high interest for medical imaging departments, as well as significantly impact deep learning research within the biomedical domain, which makes it particularly interesting for people involved in industry and researchers all along. LÄS MER