L. Jelen

Publications26
h-index7
Citations325
Highly Influential Citations14
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  • Publications
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Classification of Breast Cancer Malignancy Using Cytological Images of Fine Needle Aspiration Biopsies
TLDR
We present a framework for automatic malignancy grading of fine needle aspiration biopsy tissue based on preextracted features. Expand
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Evolutionary undersampling boosting for imbalanced classification of breast cancer malignancy
TLDR
We propose a complete, fully automatic and efficient clinical decision support system for breast cancer malignancy grading. Expand
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Web–Based Framework For Breast Cancer Classification
TLDR
This paper contains a description of the study on the quality of the various algorithms used for the segmentation and classification of breast cancer malignancy. Expand
  • 12
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Computerized cancer malignancy grading of fine needle aspirates
According to the World Health Organization, breast cancer is a leading cause of death among middle-aged women. Precise diagnosis and correct treatment significantly reduces the high number of deaths… Expand
  • 7
  • 1
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Influence of feature set reduction on breast cancer malignancy classification of fine needle aspiration biopsies
TLDR
We investigated the nature of a wide set of features extracted from biopsy images to determine their discriminatory power and cross-correlation and present an improved classification system for cancer malignancy grading. Expand
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Oversampling Methods for Classification of Imbalanced Breast Cancer Malignancy Data
TLDR
We present several state of the art methods, that are based on the oversampling approach, i.e. introduction of artificial objects into the dataset to eliminate the disproportion among classes. Expand
  • 11
Comparison of Pleomorphic and Structural Features Used for Breast Cancer Malignancy Classification
TLDR
Malignancy of a cancer is one of the most important factors that are taken into consideration during breast cancer. Expand
  • 7
One-Class Classification Decomposition for Imbalanced Classification of Breast Cancer Malignancy Data
TLDR
In this paper we address a problem arising from the classification of breast cancer malignancy data by applying state-of-the-art methods for imbalanced classification. Expand
  • 6
Influence of nuclei segmentation on breast cancer malignancy classification
TLDR
We discuss a role of nuclear segmentation from fine needle aspiration biopsy (FNA) slides and its influence on malignancy classification. Expand
  • 5
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Clinical Validation of Computerized Breast Cancer Malignancy Grading
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