Search Results for author: Marcin Grzegorzek

Found 31 papers, 2 papers with code

Skeleton Ground Truth Extraction: Methodology, Annotation Tool and Benchmarks

1 code implementation10 Oct 2023 Cong Yang, Bipin Indurkhya, John See, Bo Gao, Yan Ke, Zeyd Boukhers, Zhenyu Yang, Marcin Grzegorzek

However, most existing shape and image datasets suffer from the lack of skeleton GT and inconsistency of GT standards.

ECPC-IDS:A benchmark endometrail cancer PET/CT image dataset for evaluation of semantic segmentation and detection of hypermetabolic regions

no code implementations16 Aug 2023 Dechao Tang, Tianming Du, Deguo Ma, Zhiyu Ma, Hongzan Sun, Marcin Grzegorzek, Huiyan Jiang, Chen Li

As far as we know, this is the first publicly available dataset of endometrial cancer with a large number of multiple images, including a large amount of information required for image and target detection.

Image Segmentation object-detection +3

ACTIVE: A Deep Model for Sperm and Impurity Detection in Microscopic Videos

no code implementations15 Jan 2023 Ao Chen, Jinghua Zhang, Md Mamunur Rahaman, Hongzan Sun, M. D., Tieyong Zeng, Marcin Grzegorzek, Feng-Lei Fan, Chen Li

The accurate detection of sperms and impurities is a very challenging task, facing problems such as the small size of targets, indefinite target morphologies, low contrast and resolution of the video, and similarity of sperms and impurities.

object-detection Object Detection

Segmentation of Weakly Visible Environmental Microorganism Images Using Pair-wise Deep Learning Features

no code implementations31 Aug 2022 Frank Kulwa, Chen Li, Marcin Grzegorzek, Md Mamunur Rahaman, Kimiaki Shirahama, Sergey Kosov

The use of PDLFs enables the network to focus more on the foreground (EMs) by concatenating the pairwise deep learning features of each image to different blocks of the base model SegNet.

Specificity

A Comparative Study of Gastric Histopathology Sub-size Image Classification: from Linear Regression to Visual Transformer

no code implementations25 May 2022 Weiming Hu, HaoYuan Chen, Wanli Liu, Xiaoyan Li, Hongzan Sun, Xinyu Huang, Marcin Grzegorzek, Chen Li

Ensemble learning is a way to improve the accuracy of algorithms, and finding multiple learning models with complementarity types is the basis of ensemble learning.

BIG-bench Machine Learning Ensemble Learning +2

Application of Transfer Learning and Ensemble Learning in Image-level Classification for Breast Histopathology

no code implementations18 Apr 2022 Yuchao Zheng, Chen Li, Xiaomin Zhou, HaoYuan Chen, Hao Xu, Yixin Li, Haiqing Zhang, Xiaoyan Li, Hongzan Sun, Xinyu Huang, Marcin Grzegorzek

Method: This paper proposes a deep ensemble model based on image-level labels for the binary classification of benign and malignant lesions of breast histopathological images.

Binary Classification Classification +4

A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements

no code implementations18 Feb 2022 Jiawei Zhang, Chen Li, Md Mamunur Rahaman, YuDong Yao, Pingli Ma, Jinghua Zhang, Xin Zhao, Tao Jiang, Marcin Grzegorzek

This study has high research significance and application value, which can be referred to microbial researchers to have a comprehensive understanding of microorganism biovolume measurements using digital image analysis methods and potential applications.

Image Segmentation Semantic Segmentation

A Survey of Semen Quality Evaluation in Microscopic Videos Using Computer Assisted Sperm Analysis

no code implementations16 Feb 2022 Wenwei Zhao, Pingli Ma, Chen Li, Xiaoning Bu, Shuojia Zou, Tao Jiang, Marcin Grzegorzek

The various works related to Computer Assisted Sperm Analysis methods in the last 30 years (since 1988) are comprehensively introduced and analysed in this survey.

object-detection Object Detection

A State-of-the-art Survey of U-Net in Microscopic Image Analysis: from Simple Usage to Structure Mortification

no code implementations14 Feb 2022 Jian Wu, Wanli Liu, Chen Li, Tao Jiang, Islam Mohammad Shariful, Hongzan Sun, Xiaoqi Li, Xintong Li, Xinyu Huang, Marcin Grzegorzek

Image analysis technology is used to solve the inadvertences of artificial traditional methods in disease, wastewater treatment, environmental change monitoring analysis and convolutional neural networks (CNN) play an important role in microscopic image analysis.

Image Segmentation Segmentation +1

What Can Machine Vision Do for Lymphatic Histopathology Image Analysis: A Comprehensive Review

no code implementations21 Jan 2022 Xiaoqi Li, HaoYuan Chen, Chen Li, Md Mamunur Rahaman, Xintong Li, Jian Wu, Xiaoyan Li, Hongzan Sun, Marcin Grzegorzek

In the past ten years, the computing power of machine vision (MV) has been continuously improved, and image analysis algorithms have developed rapidly.

EMDS-7: Environmental Microorganism Image Dataset Seventh Version for Multiple Object Detection Evaluation

no code implementations11 Oct 2021 Hechen Yang, Chen Li, Xin Zhao, Bencheng Cai, Jiawei Zhang, Pingli Ma, Peng Zhao, Ao Chen, Hongzan Sun, Yueyang Teng, Shouliang Qi, Tao Jiang, Marcin Grzegorzek

The Environmental Microorganism Image Dataset Seventh Version (EMDS-7) is a microscopic image data set, including the original Environmental Microorganism images (EMs) and the corresponding object labeling files in ". XML" format file.

Object object-detection +1

A Comparison for Patch-level Classification of Deep Learning Methods on Transparent Environmental Microorganism Images: from Convolutional Neural Networks to Visual Transformers

no code implementations22 Jun 2021 Hechen Yang, Chen Li, Jinghua Zhang, Peng Zhao, Ao Chen, Xin Zhao, Tao Jiang, Marcin Grzegorzek

We conclude that ViT performs the worst in classifying 8 * 8 pixel patches, but it outperforms most convolutional neural networks in classifying 224 * 224 pixel patches.

GasHisSDB: A New Gastric Histopathology Image Dataset for Computer Aided Diagnosis of Gastric Cancer

1 code implementation4 Jun 2021 Weiming Hu, Chen Li, Xiaoyan Li, Md Mamunur Rahaman, Jiquan Ma, Yong Zhang, HaoYuan Chen, Wanli Liu, Changhao Sun, YuDong Yao, Hongzan Sun, Marcin Grzegorzek

In order to prove that the methods of different periods in the field of image classification have discrepancies on GasHisSDB, we select a variety of classifiers for evaluation.

BIG-bench Machine Learning Image Classification +1

A Comparison for Anti-noise Robustness of Deep Learning Classification Methods on a Tiny Object Image Dataset: from Convolutional Neural Network to Visual Transformer and Performer

no code implementations3 Jun 2021 Ao Chen, Chen Li, HaoYuan Chen, Hechen Yang, Peng Zhao, Weiming Hu, Wanli Liu, Shuojia Zou, Marcin Grzegorzek

In this paper, we first briefly review the development of Convolutional Neural Network and Visual Transformer in deep learning, and introduce the sources and development of conventional noises and adversarial attacks.

Classification Image Classification

A State-of-the-art Survey of Object Detection Techniques in Microorganism Image Analysis: From Classical Methods to Deep Learning Approaches

no code implementations7 May 2021 Pingli Ma, Chen Li, Md Mamunur Rahaman, YuDong Yao, Jiawei Zhang, Shuojia Zou, Xin Zhao, Marcin Grzegorzek

In this review, first, we analyse the existing microorganism detection methods in chronological order, from traditional image processing and traditional machine learning to deep learning methods.

object-detection Object Detection

GasHis-Transformer: A Multi-scale Visual Transformer Approach for Gastric Histopathological Image Detection

no code implementations29 Apr 2021 HaoYuan Chen, Chen Li, Ge Wang, Xiaoyan Li, Md Rahaman, Hongzan Sun, Weiming Hu, Yixin Li, Wanli Liu, Changhao Sun, Shiliang Ai, Marcin Grzegorzek

In this paper, a multi-scale visual transformer model, referred as GasHis-Transformer, is proposed for Gastric Histopathological Image Detection (GHID), which enables the automatic global detection of gastric cancer images.

Adversarial Attack General Classification +3

A New Pairwise Deep Learning Feature For Environmental Microorganism Image Analysis

no code implementations24 Feb 2021 Frank Kulwa, Chen Li, Jinghua Zhang, Kimiaki Shirahama, Sergey Kosov, Xin Zhao, Hongzan Sun, Tao Jiang, Marcin Grzegorzek

In order to fasten, low the cost, increase consistency and accuracy of identification, we propose the novel pairwise deep learning features to analyze microorganisms.

Specificity

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