Cervical cell classification with deep-learning algorithms

Article Chemistry, Analytical

Smartphone imaging spectrometer for egg/meat freshness monitoring

Tianci Wang et al.

Summary: With the advancement of technology, researchers have developed a portable imaging spectrometer that can transmit and process spectral data through smartphones, effectively monitoring the freshness of food samples.

ANALYTICAL METHODS (2022)

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Article Engineering, Biomedical

A hybrid model for efficient cervical cell classification

K. Sabeena et al.

Summary: An efficient automated hybrid framework was proposed in this paper to enhance the cell classification accuracy of cervical cytology images, achieving promising performance on pap stained cytology images. The integration of a Pyramid Scene Parsing Model with an ensemble-based stack classifier proved to be effective in accurately identifying cell types. The experiments demonstrated that the model achieved high accuracy and AUC for 2-class and 4-class classification tasks, showing the potential for automated cervical screening and diagnosis systems.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2022)

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Article Oncology

Comparative performance of the human papillomavirus test and cytology for primary screening for high-grade cervical intraepithelial neoplasia at the population level

Erika Hurtado-Salgado et al.

Summary: This study analyzed screening data from Mexico's public cervical cancer prevention program from 2010 to 2015, and found that hrHPV testing with cytological triage can detect twice as many CIN2+ cases compared to screening using cytology alone in women aged 35 to 64.

INTERNATIONAL JOURNAL OF CANCER (2022)

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Article Computer Science, Theory & Methods

Generative Adversarial Networks (GANs): Challenges, Solutions, and Future Directions

Divya Saxena et al.

Summary: This study provides a comprehensive survey of the advancements in design and optimization solutions for Generative Adversarial Networks (GANs). It proposes a new taxonomy to structure the solutions and discusses different GAN variants within each solution and their relationships. Promising research directions in this rapidly growing field are also presented.

ACM COMPUTING SURVEYS (2022)

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Article Spectroscopy

Open-source mobile multispectral imaging system and its applications in biological sample sensing

Fuzhou Shen et al.

Summary: Visible-near-infrared spectroscopy data is an important quantitative indicator for biomolecular analysis, and hyperspectral/multispectral imaging systems provide spatial information of the object of interest for analyzing the spatial distribution of biomolecules. This study introduces an open-source mobile multispectral imaging system, tests the influence of LED utilization on the multispectral image, and designs image-processing algorithms to correct this influence. Experimental results demonstrate the stable performance and compatibility of the system with various spectral imaging applications.

SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY (2022)

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Review Pathology

Computational Cytology: Lessons Learned from Pap Test Computer-Assisted Screening

Madelyn Lew et al.

Summary: In the face of rapid technological advances in computational cytology, the optimization of AI applications in clinical practice requires reflection on lessons learned from the long journey of developing computer-assisted Pap test screening. Several factors such as supply and demand, FDA oversight, reimbursement, learning curves, workflow changes, and cytologist apprehension play significant roles in the success or failure of automated screening technologies. Despite challenges, perseverance, workflow optimization, diagnostic accuracy improvements, and regulatory and financial approvals can facilitate the widespread adoption of new technologies in healthcare.

ACTA CYTOLOGICA (2021)

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Article Engineering, Biomedical

Workflow and hardware for intraoperative hyperspectral data acquisition in neurosurgery

Richard Muehle et al.

Summary: In order to prevent further brain tumor growth, it is important to remove malignant tissue as completely as possible in neurosurgical operations. Hyperspectral imaging can provide spatial information about brain tissue types and characteristics. Further optimization of technical aspects is needed to adapt image processing algorithms for specifying tissue quality and function based on the collected data.

BIOMEDICAL ENGINEERING-BIOMEDIZINISCHE TECHNIK (2021)

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Article Computer Science, Interdisciplinary Applications

Cervical cell classification with graph convolutional network

Jun Shi et al.

Summary: The study introduces a novel cervical cell classification method based on Graph Convolutional Network (GCN) to explore the potential relationships of cervical cell images for improving classification performance. Experimental results demonstrate the method's superiority in cervical cell classification, particularly in handling different staining conditions.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2021)

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Article Computer Science, Information Systems

DCAVN: Cervical cancer prediction and classification using deep convolutional and variational autoencoder network

Aditya Khamparia et al.

Summary: The study aims to automate cancer diagnosis and classification through deep learning techniques using the Herlev dataset, achieving high diagnostic accuracy for cervical cancer.

MULTIMEDIA TOOLS AND APPLICATIONS (2021)

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Article Computer Science, Interdisciplinary Applications

Identification of Melanoma From Hyperspectral Pathology Image Using 3D Convolutional Networks

Qian Wang et al.

Summary: The study utilized a deep convolutional network, Hyper-net, to segment melanoma from hyperspectral pathology images. The model showed improved accuracy and reduced false negative rate, demonstrating its potential in assisting pathologists with melanoma diagnosis based on hyperspectral pathology images.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2021)

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Article Health Care Sciences & Services

Top Ten Tips Palliative Care Clinicians Should Know About Caring for Patients with Cervical Cancer

Claire Hoppenot et al.

Summary: Cervical cancer is the most common gynecologic cancer worldwide, mostly related to human papillomavirus exposure. Treatment modalities include surgery, radiation therapy, and chemotherapy, which can cause symptoms like pain and bleeding. Comprehensive physical and emotional supportive care is crucial for women with cervical cancer.

JOURNAL OF PALLIATIVE MEDICINE (2021)

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Article Chemistry, Multidisciplinary

A Hierarchical Feature-Based Methodology to Perform Cervical Cancer Classification

Debora N. Diniz et al.

Summary: This study proposed a workload-reducing algorithm for cervical cancer detection based on analysis of cell nuclei features within Pap smear images. By investigating eight traditional machine learning methods, a hierarchical classification methodology was developed for computer-aided screening of cell lesions, showing Random Forest as the best classifier. The results suggest that hierarchical classification outperforms other methods such as decision trees, k-NN, and the Ridge methods.

APPLIED SCIENCES-BASEL (2021)

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Article Biology

DeepCervix: A deep learning-based framework for the classification of cervical cells using hybrid deep feature fusion techniques

Md Mamunur Rahaman et al.

Summary: Cervical cancer can be prevented and treated through manual screening and deep learning techniques. The proposed hybrid deep feature fusion technology achieved good results in classifying cervical cells.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

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Article Mathematical & Computational Biology

Generative adversarial network based data augmentation to improve cervical cell classification model

Suxiang Yu et al.

Summary: The study proposed an automatic cervical cell classification model, using a generative adversarial network to generate abnormal cell images and training a convolutional neural network. Experimental results showed that pre-training the CNN with generated images and fine-tuning with real images achieved the best performance, with an AUC value of 0.984.

MATHEMATICAL BIOSCIENCES AND ENGINEERING (2021)

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Article Computer Science, Theory & Methods

Cervical cancer classification using convolutional neural networks and extreme learning machines

Ahmed Ghoneim et al.

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE (2020)

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Article Computer Science, Hardware & Architecture

Internet of health things-driven deep learning system for detection and classification of cervical cells using transfer learning

Aditya Khamparia et al.

JOURNAL OF SUPERCOMPUTING (2020)

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Article Computer Science, Artificial Intelligence

A shape context fully convolutional neural network for segmentation and classification of cervical nuclei in Pap smear images

Elima Hussain et al.

ARTIFICIAL INTELLIGENCE IN MEDICINE (2020)

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Article Computer Science, Information Systems

Single and Clustered Cervical Cell Classification with Ensemble and Deep Learning Methods

Mohammed Kuko et al.

INFORMATION SYSTEMS FRONTIERS (2020)

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Article Computer Science, Hardware & Architecture

Generative Adversarial Networks

Ian Goodfellow et al.

COMMUNICATIONS OF THE ACM (2020)

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Article Computer Science, Artificial Intelligence

Detection of cervical cancer cells based on strong feature CNN-SVM network

A. Dongyao Jia et al.

NEUROCOMPUTING (2020)

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Article Engineering, Multidisciplinary

An Automatic Mass Screening System for Cervical Cancer Detection Based on Convolutional Neural Network

Aziz-ur Rehman et al.

MATHEMATICAL PROBLEMS IN ENGINEERING (2020)

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Proceedings Paper Computer Science, Software Engineering

Automatic Classification of Cervical Cell Patches based on Non-geometric Characteristics

Douglas Wender A. Isidoro et al.

PROCEEDINGS OF THE 15TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS, VOL 5: VISAPP (2020)

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Article Computer Science, Artificial Intelligence