Wykaz publikacji wybranego autora

Marek Wodziński, dr inż.

adiunkt

Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej
WEAIiIB-kmie, Katedra Metrologii i Elektroniki

  • 2018

    [dyscyplina 1] dziedzina nauk inżynieryjno-technicznych / inżynieria biomedyczna

Identyfikatory Autora Informacje o Autorze w systemach zewnętrznych

ORCID: 0000-0002-8076-6246 orcid iD

ResearcherID: V-7804-2017

Scopus: 57195258893

PBN: 5e70929a878c28a047398dfe

OPI Nauka Polska

System Informacyjny AGH (SkOs)

Liczba pozycji spełniających powyższe kryteria selekcji: 49, z ogólnej liczby 49 publikacji Autora

1
  • A multi-task multiple instance learning algorithm to analyze large whole slide images from bright challenge 2022
2
  • Adversarial affine registration for real-time intraoperative registration of 3-D US-US for brain shift correction
3
  • An AI‑based algorithm for the automatic evaluation of image quality in canine thoracic radiographs
4
  • An $Al-based$ algorithm for the automatic classification of thoracic radiographs in cats
5
  • ANHIR: Automatic Non-rigid Histological Image Registration challenge
6
  • Application of B-splines FFD image registration in breast cancer radiotherapy planning
7
  • Application of Demons image registration algorithms in resected breast cancer lodge localization
8
  • Artifact augmentation for learning-based quality control of whole slide images
9
  • Artificial CT data generation method with known ground-truth for image registration with missing data
10
  • Automatic aorta segmentation with heavily augmented, high-resolution 3-D ResUNet: contribution to the SEG.A challenge
11
  • Automatic classification of canine thoracic radiographs using deep learning
12
  • Automatic quality assessment of reflectance confocal microscopy mosaics using attention-based deep neural network
13
  • Contact-free multispectral identity verification system using palm veins and deep neural network
14
  • Convolutional Neural Network approach to classify skin lesions using reflectance confocal microscopy
15
  • Data-driven color augmentation for H&E stained images in computational pathology
16
  • Deep generative networks for heterogeneous augmentation of cranial defects
17
  • Deep learning approach to Parkinson’s disease detection using voice recordings and Convolutional Neural Network dedicated to image classification
18
  • Deep learning-based framework for automatic cranial defect reconstruction and implant modeling
19
20
  • Development of an artificial intelligence-based method for the diagnosis of the severity of myxomatous mitral valve disease from canine chest radiographs
21
  • DRU-Net: pulmonary artery segmentation via dense residual U-network with hybrid loss function
22
  • High-resolution cranial defect reconstruction by iterative, low-resolution, point cloud completion transformers
23
  • Improving oncoplastic breast tumor bed localization for radiotherapy planning using image registration algorithms
24
  • Improving the automatic cranial implant design in cranioplasty by linking different datasets
25
  • Improving the classification of veterinary thoracic radiographs through inter-species and inter-pathology self-supervised pre-training of deep learning models