↓ Skip to main content
What is this page? Embed badge

Medical Image Learning with Limited and Noisy Data

Overview of attention for book
Cover of 'Medical Image Learning with Limited and Noisy Data'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Heatmap Regression for Lesion Detection Using Pointwise Annotations
  3. Altmetric Badge
    Chapter 2 Partial Annotations for the Segmentation of Large Structures with Low Annotation Cost
  4. Altmetric Badge
    Chapter 3 Abstraction in Pixel-wise Noisy Annotations Can Guide Attention to Improve Prostate Cancer Grade Assessment
  5. Altmetric Badge
    Chapter 4 Meta Pixel Loss Correction for Medical Image Segmentation with Noisy Labels
  6. Altmetric Badge
    Chapter 5 Re-thinking and Re-labeling LIDC-IDRI for Robust Pulmonary Cancer Prediction
  7. Altmetric Badge
    Chapter 6 Universal Lesion Detection and Classification Using Limited Data and Weakly-Supervised Self-training
  8. Altmetric Badge
    Chapter 7 BoxShrink: From Bounding Boxes to Segmentation Masks
  9. Altmetric Badge
    Chapter 8 Multi-Feature Vision Transformer via Self-Supervised Representation Learning for Improvement of COVID-19 Diagnosis
  10. Altmetric Badge
    Chapter 9 SB-SSL: Slice-Based Self-supervised Transformers for Knee Abnormality Classification from MRI
  11. Altmetric Badge
    Chapter 10 Optimizing Transformations for Contrastive Learning in a Differentiable Framework
  12. Altmetric Badge
    Chapter 11 Stain Based Contrastive Co-training for Histopathological Image Analysis
  13. Altmetric Badge
    Chapter 12 CLINICAL: Targeted Active Learning for Imbalanced Medical Image Classification
  14. Altmetric Badge
    Chapter 13 Real Time Data Augmentation Using Fractional Linear Transformations in Continual Learning
  15. Altmetric Badge
    Chapter 14 DIAGNOSE: Avoiding Out-of-Distribution Data Using Submodular Information Measures
  16. Altmetric Badge
    Chapter 15 Auto-segmentation of Hip Joints Using MultiPlanar UNet with Transfer Learning
  17. Altmetric Badge
    Chapter 16 Asymmetry and Architectural Distortion Detection with Limited Mammography Data
  18. Altmetric Badge
    Chapter 17 Class Imbalance Correction for Improved Universal Lesion Detection and Tagging in CT
  19. Altmetric Badge
    Chapter 18 CVAD: An Anomaly Detector for Medical Images Based on Cascade VAE
  20. Altmetric Badge
    Chapter 19 Visual Field Prediction with Missing and Noisy Data Based on Distance-Based Loss
  21. Altmetric Badge
    Chapter 20 Image Quality Classification for Automated Visual Evaluation of Cervical Precancer
  22. Altmetric Badge
    Chapter 21 A Monotonicity Constrained Attention Module for Emotion Classification with Limited EEG Data
  23. Altmetric Badge
    Chapter 22 Automated Skin Biopsy Analysis with Limited Data
Attention for Chapter 20: Image Quality Classification for Automated Visual Evaluation of Cervical Precancer
Altmetric Badge

Mentioned by

twitter
2 X users

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
3 Mendeley
Summary X Dimensions citations
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
Image Quality Classification for Automated Visual Evaluation of Cervical Precancer
Chapter number 20
Book title
Medical Image Learning with Limited and Noisy Data
Published by
Springer, Cham, January 2022
DOI 10.1007/978-3-031-16760-7_20
Pubmed ID
36315110
Book ISBNs
978-3-03-116759-1, 978-3-03-116760-7
Authors

Xue, Zhiyun, Angara, Sandeep, Guo, Peng, Rajaraman, Sivaramakrishnan, Jeronimo, Jose, Rodriguez, Ana Cecilia, Alfaro, Karla, Charoenkwan, Kittipat, Mungo, Chemtai, Domgue, Joel Fokom, Wentzensen, Nicolas, Desai, Kanan T., Ajenifuja, Kayode Olusegun, Wikström, Elisabeth, Befano, Brian, Sanjosé, Silvia, Schiffman, Mark, Antani, Sameer, de Sanjosé, Silvia

View on publisher site
X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 33%
Student > Doctoral Student 1 33%
Unknown 1 33%
Readers by discipline Count As %
Medicine and Dentistry 1 33%
Engineering 1 33%
Unknown 1 33%

This page is provided by Altmetric.