Omslagsbillede

Supervised and Semi-supervised Multi-structure Segmentation and Landmark Detection in Dental Data MICCAI 2024 Challenges: ToothFairy 2024, 3DTeethLand 2024, and STS 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings /

This book constitutes three challenges that were held in conjunction with the 27th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2024, in Marrakesh, Morocco, on October 6, 2024: ToothFairy challenge(ToothFairy2: Multi-Structure Segmentation in CBCT Vo...

Fuld beskrivelse

Saved in:
Bibliografiske detaljer
Institution som forfatter: SpringerLink (Online service)
Andre forfattere: Wang, Yaqi (Editor), Qian, Dahong (Editor), Wang, Shuai (Editor), Ben-Hamadou, Achraf (Editor), Pujades, Sergi (Editor), Lumetti, Luca (Editor), Grana, Costantino (Editor), Bolelli, Federico (Editor)
Format: Electronisk eBog
Sprog:engelsk
Udgivet: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Udgivelse:1st ed. 2025.
Serier:Lecture Notes in Computer Science, 15571
Fag:
Image processing > Digital techniques.
Computer vision.
Computers.
Application software.
Machine learning.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Computing Milieux.
Computer and Information Systems Applications.
Machine Learning.
Online adgang:https://doi.org/10.1007/978-3-031-88977-6
Tags: Tilføj Tag
Ingen Tags, Vær først til at tagge denne postø!
Indholdsfortegnelse:
  • ToothFairy2: Multi-Structure Segmentation in CBCT Volumes
  • Inferior Alveolar Nerve Segmentation in CBCT Images Using Connectivity-based Selective Re-training
  • Scaling nnU-Net for CBCT Segmentation
  • DiENTeS: Dynamic ENTity Segmentation with Local-Global Transformers
  • Enhanced Multi-Structure Segmentation in CBCT Images with Adaptive Structure Optimization
  • Weakly-Supervised Convolutional Neural Networks for Inferior Alveolar Nerve Segmentation in CBCT images
  • A Multi-Axial Network for Oral Structural Segmentation
  • Automatic Multi-Structure Segmentation in Cone Beam Computed Tomography Volumes Using Deep Encoder-Decoder Architectures
  • Video Foundation Model for Medical 3D Segmentation
  • STS: Semi-supervised Teeth Segmentation
  • A Two-Stage Semi-Supervised nnU-Net Model for Automated Tooth Segmentation in Panoramic X-ray Images
  • Two-Stage Semi-Supervised nnU-Net Framework for Tooth Segmentation in CBCT Images
  • SemiT-SAM: Building a Visual Foundation Model for Tooth Instance Segmentation on Panoramic Radiographs
  • Multi-stage Dental Visual Detection Based on YOLOv8: Dental 3D CBCT
  • Efficient Semi-Supervised Tooth Instance Segmentation in Panoramic X-rays Using ResUnet50 and SAM Networks
  • DAE-Net: Dual Attention Embedding-based Tooth Instance Segmentation Approach for Panoramic X-ray Images
  • A Self-Training Pipeline for Semi-Supervised 2D Teeth Instance Segmentation
  • Deformable Inherent Consistent Learning Network for Accurate Tooth Segmentation in Dental Panoramic Radiographs
  • Semi-Supervised 2D Dental Image Segmentation via Cross Teaching Network
  • A Novel Two-Stage Approach for 3D Dental Tooth Instance Segmentation
  • 3DTeethLand24: 3D Teeth Landmarks Detection Challenge
  • A Two-Stage Framework with Dual-Branch Network for End-to-End 3D Tooth Landmark Detection
  • Leveraging Point Transformers for Detecting Anatomical Landmarks in Digital Dentistry
  • ToothInstanceNet: Comprehensive Information from Intra-Oral Scans by Integration of Large-Context and High-Resolution Predictions.

Lignende værker