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Artificial Intelligence in Pancreatic Disease Detection and Diagnosis, and Personalized Incremental Learning in Medicine First International Workshop, AIPAD 2024 and First International Workshop, PILM 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings /

This volume constitutes the refereed proceedings of the First International Workshop on Artificial Intelligence in Pancreatic Disease Detection and Diagnosis, AIPAD 2024 and the First International Workshop on Personalized Incremental Learning in Medicine, PILM 2024, held in conjunction with MICCAI...

Täydet tiedot

Tallennettuna:
Bibliografiset tiedot
Yhteisötekijä: SpringerLink (Online service)
Muut tekijät: Proietto Salanitri, Federica (Toimittaja), Viriri, Serestina (Toimittaja), Bağcı, Ulaş (Toimittaja), Tiwari, Pallavi (Toimittaja), Gong, Boqing (Toimittaja), Spampinato, Concetto (Toimittaja), Palazzo, Simone (Toimittaja), Bellitto, Giovanni (Toimittaja), Zlatintsi, Nancy (Toimittaja), Filntisis, Panagiotis (Toimittaja), Lee, Cecilia S. (Toimittaja), Lee, Aaron Y. (Toimittaja)
Aineistotyyppi: Elektroninen E-kirja
Kieli:englanti
Julkaistu: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Painos:1st ed. 2025.
Sarja:Lecture Notes in Computer Science, 15197
Aiheet:
Machine learning.
Machine Learning.
Linkit:https://doi.org/10.1007/978-3-031-73483-0
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Sisällysluettelo:
  • Artificial Intelligence in Pancreatic Disease Detection and Diagnosis
  • Assessing the Efficacy of Foundation Models in Pancreas Segmentation
  • Hybrid Deep Learning Model for Pancreatic Cancer Image Segmentation
  • Leveraging SAM and Learnable Prompts for Pancreatic MRI Segmentation
  • Optimizing Synthetic Data for Enhanced Pancreatic Tumor Segmentation
  • Pancreatic Vessel Landmark Detection in CT Angiography using Prior Anatomical Knowledge
  • Personalized Incremental Learning in Medicine.-Addressing Catastrophic Forgetting by Modulating Global Batch Normalization Statistics for Medical Domain Expansion
  • Distribution-Aware Replay for Continual MRI Segmentation
  • Exploring Wearable Emotion Recognition with Transformer-Based Continual Learning.

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