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Role of AI and Histopathological Images in Detecting Prostate Cancer: A Survey

Sarah M. Ayyad, Mohamed Shehata, Ahmed Shalaby, Mohamed Abou El-Ghar, Mohammed Ghazal, Moumen El-Melegy, Nahla B. Abdel-Hamid, Labib M. Labib, H. Arafat Ali, Ayman El-Baz
2021 Sensors  
However, there is a lack of comprehensive surveys that focus on prostate cancer using histopathology images.  ...  Histopathological image diagnosis is a gold standard for detecting prostate cancer as it has different visual characteristics but interpreting those type of images needs a high level of expertise and takes  ...  Acknowledgments: Authors like to acknowledge the support of the Academy of Scientific Research and Technology in Egypt in this work.  ... 
doi:10.3390/s21082586 pmid:33917035 fatcat:qfspvswivrbnlaih5y4gun5zwm

The Use of Digital Pathology and Artificial Intelligence in Histopathological Diagnostic Assessment of Prostate Cancer: A Survey of Prostate Cancer UK Supporters

Kai Rakovic, Richard Colling, Lisa Browning, Monica Dolton, Margaret R. Horton, Andrew Protheroe, Alastair D. Lamb, Richard J. Bryant, Richard Scheffer, James Crofts, Ewart Stanislaus, Clare Verrill
2022 Diagnostics  
Prostate Cancer UK supporters were invited to an online survey which included quantitative and qualitative questions exploring views on the use of DP and AI in histopathological assessment.  ...  There has been particular interest in the deployment of digital pathology (DP) and artificial intelligence (AI) in the diagnosis of prostate cancer, but little is known about the views of the public on  ...  One area of pathology where there has been intense interest in AI is in prostate cancer (PCa).  ... 
doi:10.3390/diagnostics12051225 pmid:35626380 pmcid:PMC9141178 fatcat:3vstbm3q7bhvdboo4nsyzlbhja

Deep neural network models for computational histopathology: A survey [article]

Chetan L. Srinidhi, Ozan Ciga, Anne L. Martel
2019 arXiv   pre-print
In this paper, we present a comprehensive review of state-of-the-art deep learning approaches that have been used in the context of histopathological image analysis.  ...  Recently, deep learning has become the mainstream methodological choice for analyzing and interpreting cancer histology images.  ...  The addition of multi-scale and contextual knowledge into CNN plays an essential role in identifying overlapping cell structures in histopathology images.  ... 
arXiv:1912.12378v1 fatcat:xdfkzzwzb5alhjfhffqpcurb2u

A survey on computational intelligence approaches for predictive modeling in prostate cancer

Georgina Cosma, David Brown, Matthew Archer, Masood Khan, A. Graham Pockley
2017 Expert systems with applications  
This paper provides a survey of recent work on computational intelligence approaches that have been applied to prostate cancer predictive modeling, and considers the challenges which need to be addressed  ...  cancer predictive models, and the suitability of these approaches are discussed.  ...  A hybrid Neural Network and Support Vector Machine system has been embedded in a Computer-Aided Diagnosis (CAD) tool for predicting the Gleason Grade of prostate cancer using histopathology images (Greenblatt  ... 
doi:10.1016/j.eswa.2016.11.006 fatcat:ii6gbq6qcbai5kxvcy4l7kkg54

The Application of Deep Convolutional Neural Networks to Brain Cancer Images: A Survey

Amin Zadeh Shirazi, Eric Fornaciari, Mark D. McDonnell, Mahdi Yaghoobi, Yesenia Cevallos, Luis Tello-Oquendo, Deysi Inca, Guillermo A. Gomez
2020 Journal of Personalized Medicine  
and histopathological imaging (H&E) clinical information.  ...  current challenges in the field for the broader applicability of DCNN in personalized brain cancer care by focusing on two main applications of DCNNs: classification and segmentation of brain cancer tumors  ...  Introduction Artificial Intelligence (AI)and Machine Learning (ML) methods play a critical role in industrial processes [1] [2] [3] and biomedicine [4] [5] [6] [7] .  ... 
doi:10.3390/jpm10040224 pmid:33198332 pmcid:PMC7711876 fatcat:lwfgkwj5trd3beaodeucuzd5ou

A Review on Prostate Cancer Detection using CNN

Merlyn Koonamparampath, Raj Shah, Mahipal Sundvesha, Meena Ugale
2022 International Journal for Research in Applied Science and Engineering Technology  
We give a review of the usage of CNN applied to several automatic processing tasks of prostate cancer detection and diagnosis, to provide an overview of the progress in this field, based on the increased  ...  Using AI to manage prostate cancer would have a significant influence on healthcare.  ...  The authors would like to extend their gratitude to the guidance and support received from Meena Ugale and colleagues from the IT Department, Xavier Institute of Engineering, Mumbai, India.  ... 
doi:10.22214/ijraset.2022.40747 fatcat:inl6l6uaofcevinxyzlyilvbjm

Diffusion weighted magnetic resonance imaging and its recent trend-a survey

Geetha Soujanya Chilla, Cher Heng Tan, Chenjie Xu, Chueh Loo Poh
2015 Quantitative Imaging in Medicine and Surgery  
This review article provides a brief introduction of diffusion weighted magnetic resonance imaging, challenges involved and recent advancements.  ...  Since its inception in 1985, diffusion weighted magnetic resonance imaging has been evolving and is becoming instrumental in diagnosis and investigation of tissue functions in various organs including  ...  The ADC maps are derived from DW images of b-values 50 and 1,000, in a prostate cancer patient.  ... 
doi:10.3978/j.issn.2223-4292.2015.03.01 pmid:26029644 pmcid:PMC4426106 fatcat:nqsnmywcwrdfrozafxj6r3piaa

A Systematic Review of Artificial Intelligence in Prostate Cancer

Derek J Van Booven, Manish Kuchakulla, Raghav Pai, Fabio S Frech, Reshna Ramasahayam, Pritika Reddy, Madhumita Parmar, Ranjith Ramasamy, Himanshu Arora
2021 Research and Reports in Urology  
Thus, this systematic review focuses on analyzing advancements in AI-based artificial neural networks (ANN) and their current role in prostate cancer diagnosis and management.  ...  The diagnosis and management of prostate cancer involves the interpretation of data from multiple modalities to aid in decision making.  ...  Disclosure The authors report no conflicts of interest for this work. Declaration of interests: the authors declare no competing interests.  ... 
doi:10.2147/rru.s268596 pmid:33520879 pmcid:PMC7837533 fatcat:a2eecsaqmza47lmubnfsahs6wq

Recent Developments in Artificial Intelligence-Based Techniques for Prostate Cancer Detection: A Scoping Review [chapter]

Uzair Shah, Md. Rafuil Biswas, Mahmood Saleh Alzubaidi, Hazrat Ali, Tanvir Alam, Mowafa Househ, Zubair Shah
2022 Studies in Health Technology and Informatics  
This review article presents a summary of the AI methods that detect and diagnose prostate cancer using different medical imaging modalities.  ...  Recently, there has been a sharp increase in the literature on AI techniques for prostate cancer diagnosis.  ...  This short review will serve as a quick reference for readers interested in studying and researching the role of AI methods in treating prostate cancer.  ... 
doi:10.3233/shti210911 pmid:35062144 fatcat:saogm7z3xfh5zmcewgfaeyld3e

Artificial Intelligence in Cancer Research and Precision Medicine

Bhavneet Bhinder, Coryandar Gilvary, Neel S. Madhukar, Olivier Elemento
2021 Cancer Discovery  
Here, we review the recent enormous progress in the application of AI to oncology, highlight limitations and pitfalls, and chart a path for adoption of AI in the cancer clinic.  ...  As these advances start penetrating the clinic, we foresee a shifting paradigm in cancer care becoming strongly driven by AI.  ...  Elemento is supported by NIH grants UL1TR002384 and R01CA194547, and the Leukemia and Lymphoma Society Specialized Center of Research grants 180078-02 and 7021-20.  ... 
doi:10.1158/ pmid:33811123 pmcid:PMC8034385 fatcat:x42n62qmrva2zodrxj4tf7bveq

A survey on deep learning in medical image analysis

Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Mohsen Ghafoorian, Jeroen A.W.M. van der Laak, Bram van Ginneken, Clara I. Sánchez
2017 Medical Image Analysis  
We survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks and provide concise overviews of studies per application area.  ...  Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images.  ...  ArXiv was searched for papers mentioning one of a set of terms related to medical imaging.  ... 
doi:10.1016/ pmid:28778026 fatcat:esbj72ftwvbgzh6jgw367k73j4

Federated Learning for Smart Healthcare: A Survey [article]

Dinh C. Nguyen, Quoc-Viet Pham, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne, Zihuai Lin, Octavia A. Dobre, Won-Joo Hwang
2021 arXiv   pre-print
Accordingly, we provide a comprehensive survey on the use of FL in smart healthcare.  ...  Subsequently, we provide a state-of-the-art review on the emerging applications of FL in key healthcare domains, including health data management, remote health monitoring, medical imaging, and COVID-19  ...  Through the simulations on prostate cancer-related images, the proposed FL scheme can yield an accuracy score of 0.9722, achieving a performance enhancement by 0.13% in comparison to non-FL schemes.  ... 
arXiv:2111.08834v1 fatcat:jmex4e25rbgy3bk67iolrj4uee

Computational pathology in ovarian cancer

Sandra Orsulic, Joshi John, Ann E. Walts, Arkadiusz Gertych
2022 Frontiers in Oncology  
Despite a dire need for improvements in ovarian cancer prevention, early detection, and treatment, the ovarian cancer field has lagged behind other cancers in the application of computational pathology  ...  Histopathologic evaluations of tissue sections are key to diagnosing and managing ovarian cancer.  ...  Similarly, an AI system has reached a clinically acceptable level of cancer detection accuracy in prostate needle biopsies (76) .  ... 
doi:10.3389/fonc.2022.924945 pmid:35965569 pmcid:PMC9372445 fatcat:oookkew2svfrxo27guezqzdvci

Machine Learning and Its Application in Skin Cancer

Kinnor Das, Clay J. Cockerell, Anant Patil, Paweł Pietkiewicz, Mario Giulini, Stephan Grabbe, Mohamad Goldust
2021 International Journal of Environmental Research and Public Health  
Although it has a significant role in the detection of skin cancer, dermatology skill lags behind radiology in terms of AI acceptance.  ...  With continuous spread, use, and emerging technologies, AI is becoming more widely available even to the general population. AI can be of use for the early detection of skin cancer.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/ijerph182413409 pmid:34949015 pmcid:PMC8705277 fatcat:dvmastcq5rgxdn7izt7brlg7iq

Self-supervised learning methods and applications in medical imaging analysis: A survey [article]

Saeed Shurrab, Rehab Duwairi
2021 arXiv   pre-print
The availability of high quality annotated medical imaging datasets is a major problem that collides with machine learning applications in the field of medical imaging analysis and impedes its advancement  ...  The article covers a set of the most recent self-supervised learning methods from the computer vision field as they are applicable to the medical imaging analysis and categorize them as predictive, generative  ...  For the latter task, Out of histopathological image stained with Hematoxylin and Eosin, the role of the task is to predict the first channel from the the stained image.  ... 
arXiv:2109.08685v2 fatcat:iu2zanqqrnaflawcxndb6xszgu
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