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Special Issue: Emerging Technologies for Medical Imaging Diagnostics, Monitoring and Therapy of Cancers

Mohsen Beheshti, Felix M. Mottaghy
2021 Journal of Clinical Medicine  
Molecular imaging and therapy play an increasingly important role in the field of "precision medicine" as an emergent prospect for management of the cancerous disease [...]  ...  Furthermore, the translation of artificial intelligence and deep learning into the clinical setting has been discussed in different articles.  ...  With the exponential development and integration of artificial intelligence (AI) and deep learning (DL) that provide promising new aspects for improving patient care, four articles in this Special Issue  ... 
doi:10.3390/jcm10061327 pmid:33806986 pmcid:PMC8005165 fatcat:dislpf3qyvegzkio4jrazmn5bm

PROMISE CLIP Project: A Retrospective, Multicenter Study for Prostate Cancer that Integrates Clinical, Imaging and Pathology Data

Jihwan Park, Mi Jung Rho, Yong Hyun Park, Chan Kwon Jung, Yosep Chong, Choung-Soo Kim, Heounjeong Go, Seong Soo Jeon, Minyong Kang, Hak Jong Lee, Sung Il Hwang, Ji Youl Lee
2019 Applied Sciences  
We initiated the PROstate Medical Intelligence System Enterprise-Clinical, Imaging, and Pathology (PROMISE CLIP) and a multicenter, big data study to develop PCa SW for patients with PCa and clinicians  ...  For this to be accomplished, diverse medical data need to be integrated with the development of intelligent software (SW) based on various types of medical data.  ...  The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.  ... 
doi:10.3390/app9152982 fatcat:u7kdqmvbdbcr7agxt5povysivm

ESUR/ESUI position paper: developing artificial intelligence for precision diagnosis of prostate cancer using magnetic resonance imaging

Tobias Penzkofer, Anwar R. Padhani, Baris Turkbey, Masoom A. Haider, Henkjan Huisman, Jochen Walz, Georg Salomon, Ivo G. Schoots, Jonathan Richenberg, Geert Villeirs, Valeria Panebianco, Olivier Rouviere (+2 others)
2021 European Radiology  
Artificial intelligence developments are essential to the successful deployment of community-wide, MRI-driven prostate cancer diagnosis.  ...  Since all current artificial intelligence / computer-aided detection systems for prostate cancer detection are experimental, multiple developmental efforts are still needed to bring the vision to fruition  ...  Characteristics of artificial intelligence systems for prostate MRI in cancer diagnosis Definition of terms Artificial intelligence (AI) is a broad field encompassing several technologies which deduce  ... 
doi:10.1007/s00330-021-08021-6 pmid:33991226 pmcid:PMC8589789 fatcat:4e42tpcx4ndutfkjx5zsyl4ooy

Radiotherapy Treatment Planning in the Age of AI: Are We Ready Yet?

Dandan Zheng, Julian C. Hong, Chunhao Wang, Xiaofeng Zhu
2019 Technology in Cancer Research and Treatment  
In this challenge, the clinical task was to detect cancer on multiparametric magnetic resonance images from suspicious prostate lesions that included both cancer and benign lesions.  ...  The applicability of their method was demonstrated on a cohort of patients having prostate cancer treated with IMRT.  ... 
doi:10.1177/1533033819894577 pmid:31858890 pmcid:PMC6927195 fatcat:rzxmizdk65hizfpbkmwm6j6otq

More than Meets the Eye: Using Textural Analysis and Artificial Intelligence as Decision Support Tools in Prostate Cancer Diagnosis—A Systematic Review

Teodora Telecan, Iulia Andras, Nicolae Crisan, Lorin Giurgiu, Emanuel Darius Căta, Cosmin Caraiani, Andrei Lebovici, Bianca Boca, Zoltan Balint, Laura Diosan, Monica Lupsor-Platon
2022 Journal of Personalized Medicine  
(1) Introduction: Multiparametric magnetic resonance imaging (mpMRI) is the main imagistic tool employed to assess patients suspected of harboring prostate cancer (PCa), setting the indication for targeted  ...  The past decade has been marked by the emerging domain of radiomics and artificial intelligence (AI), with extended application in medical diagnosis and treatment processes. (2) Aim: To present the current  ...  Discussion We aimed to highlight the progress of artificial intelligence and its use in daily clinical practice, being a valuable tool for diagnosing and staging prostate cancer.  ... 
doi:10.3390/jpm12060983 fatcat:i7hukvcxcjb6tdqxisbnhq75vm

Current Value of Biparametric Prostate MRI with Machine-Learning or Deep-Learning in the Detection, Grading, and Characterization of Prostate Cancer: A Systematic Review

Henrik J. Michaely, Giacomo Aringhieri, Dana Cioni, Emanuele Neri
2022 Diagnostics  
The intention of this review is to analyze the current value of biparametric prostate MRI in combination with methods of machine-learning and deep learning in the detection, grading, and characterization  ...  Prostate cancer detection with magnetic resonance imaging is based on a standardized MRI-protocol according to the PI-RADS guidelines including morphologic imaging, diffusion weighted imaging, and perfusion  ...  The aim of this study is to elucidate the status of artificial intelligence in prostate imaging with a focus on the so-called bi-parametric (bp) approach of prostate MRI (bpMRI).  ... 
doi:10.3390/diagnostics12040799 pmid:35453847 pmcid:PMC9027206 fatcat:g5ccvmzqqjh2tkdzugtwxm3o6y

Artificial Intelligence (AI)-based Medical Image Segmentation for 3D Printing and Naked Eye 3D Visualization

Guang JIA, Xunan HUANG, Sen TAO, Xianghuai ZHANG, Yue ZHAO, Hongcai WANG, Jie HE, Jiaxue HAO, Bo LIU, Jiejing ZHOU, Tanping LI, Xiaoling ZHANG (+1 others)
2021 Intelligent Medicine  
YOLOV3 algorithm was used to recognize prostate organ from T2-weighted MRI images with proper training. Prostate cancer and bladder cancer were segmented based on U-net from MRI images.  ...  Recently, with the development of artificial intelligence (AI) technology, tumors or organs can be quickly and accurately detected and automatically contoured from medical images.  ...  Bladder cancer MRI analysis Deep learning methods based on convolutional neural networks can be applied to T2-weighted MRI for automatic classification and segmentation of bladder cancer ( Figure 7 )  ... 
doi:10.1016/j.imed.2021.04.001 fatcat:akbe3djy2zhuxbeck4d6qlmuiy

Identification of Tumor-Specific MRI Biomarkers Using Machine Learning (ML)

Rima Hajjo, Dima A Sabbah, Sanaa K Bardaweel, Alexander Tropsha
2021 Diagnostics  
We focus on all aspects of MRI biomarkers, starting from MRI data collection, preprocessing and machine learning methods, and ending with summarizing the types of existing biomarkers and their clinical  ...  However, the latest advancements in machine learning (ML) and artificial intelligence (AI) have enabled the identification of highly predictive, disease-specific biomarkers.  ...  Deep Learning Deep learning which is also known as deep neural network (DNNs), or deep structured learning, is a machine learning method based on artificial neural networks which allows computational models  ... 
doi:10.3390/diagnostics11050742 pmid:33919342 pmcid:PMC8143297 fatcat:d5k6655lbfamzhjleyso5q54u4

Artificial Intelligence Based Algorithms for Prostate Cancer Classification and Detection on Magnetic Resonance Imaging: A Narrative Review

Jasper J. Twilt, Kicky G. van Leeuwen, Henkjan J. Huisman, Jurgen J. Fütterer, Maarten de Rooij
2021 Diagnostics  
Due to the upfront role of magnetic resonance imaging (MRI) for prostate cancer (PCa) diagnosis, a multitude of artificial intelligence (AI) applications have been suggested to aid in the diagnosis and  ...  Studies showed large heterogeneity in cohort sizes, ranging between 18 to 499 patients (median = 162) combined with different approaches for performance validation.  ...  The search was limited to articles written in English from 2018 to February 2021 using combined terms: artificial intelligence, machine learning, prostate cancer, magnetic resonance imaging, and corresponding  ... 
doi:10.3390/diagnostics11060959 pmid:34073627 fatcat:6d4r4eu2drbdxodlj77ga6xuyi

Magnetic Resonance Imaging Based Radiomic Models of Prostate Cancer: A Narrative Review

Ahmad Chaddad, Michael Kucharczyk, Abbas Cheddad, Sharon Clarke, Lama Hassan, Shuxue Ding, Saima Rathore, Mingli Zhang, Yousef Katib, Boris Bahoric, Gad Abikhzer, Stephan Probst (+1 others)
2021 Cancers  
Other potential impacts of artificial intelligence on the personalized treatment of PCa will also be discussed.  ...  The management of prostate cancer (PCa) is dependent on biomarkers of biological aggression. This includes an invasive biopsy to facilitate a histopathological assessment of the tumor's grade.  ...  Novel artificial intelligence system increases the detection of prostate cancer in whole slide images of core needle biopsies. Mod. Pathol. 2020, 33, 2058-2066. [CrossRef] [PubMed] 37.  ... 
doi:10.3390/cancers13030552 pmid:33535569 pmcid:PMC7867056 fatcat:tsyj3gt4mjax5cad5xxyxuo4jy

A Transfer Learning Approach for Automated Segmentation of Prostate Whole Gland and Transition Zone in Diffusion Weighted MRI [article]

Saman Motamed, Isha Gujrathi, Dominik Deniffel, Anton Oentoro, Masoom A. Haider, Farzad Khalvati
2020 arXiv   pre-print
In this work, we propose a transfer learning method based on a modified U-net architecture and loss function, for segmentation of prostate whole gland and transition zone in DWIs using a CNN pretrained  ...  The segmentation of prostate whole gland and transition zone in Diffusion Weighted MRI (DWI) are the first step in designing computer-aided detection algorithms for prostate cancer.  ...  IG, DD, AO, and MAH contributed in collecting and reviewing the data. SM and FK contributed to the design and implementation of machine learning modules.  ... 
arXiv:1909.09541v2 fatcat:vp4ctox3wzahdjcb4ufxm4qrwq

Deep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR

Stefano Trebeschi, Joost J. M. van Griethuysen, Doenja M. J. Lambregts, Max J. Lahaye, Chintan Parmar, Frans C. H. Bakers, Nicky H. G. M. Peters, Regina G. H. Beets-Tan, Hugo J. W. L. Aerts
2017 Scientific Reports  
Here, we evaluate deep learning methods for automatic localization and segmentation of rectal cancers on multiparametric MR imaging.  ...  Our results demonstrate that deep learning can perform accurate localization and segmentation of rectal cancer in MR imaging in the majority of patients.  ...  This work was carried out on the Dutch national e-infrastructure with the support of SURF Cooperative.  ... 
doi:10.1038/s41598-017-05728-9 pmid:28706185 pmcid:PMC5509680 fatcat:ydkwgmde6zhulewg7s44iz7p3a

Design of an Ultrasound-Navigated Prostate Cancer Biopsy System for Nationwide Implementation in Senegal

Gabor Fichtinger, Parvin Mousavi, Tamas Ungi, Aaron Fenster, Purang Abolmaesumi, Gernot Kronreif, Juan Ruiz-Alzola, Alain Ndoye, Babacar Diao, Ron Kikinis
2021 Journal of Imaging  
NaviPBx integrates concepts and methods that have been independently validated previously in clinical feasibility studies and deploys them together in a practical prostate cancer biopsy system.  ...  NaviPBx is based entirely on free open-source software and will be shared as a free open-source program with no restriction on its use.  ...  Machine learning (ML) and artificial intelligence (AI) functions for training and invoking deep learning neural networks are grouped in the SlicerAIGT extension package.  ... 
doi:10.3390/jimaging7080154 pmid:34460790 fatcat:zwashzydbjdqhcobrlxbh3pyh4

Application of U-Net based Multiparameter Magnetic Resonance Image Fusion in the Diagnosis of Prostate Cancer

Xunan Huang, Bo Zhang, Xiaoling Zhang, Min Tang, Qiguang Miao, Tanping Li, Guang Jia
2021 IEEE Access  
Experimental results show that the fusion method can enhance the appearance of prostate cancer in terms of both visual quality and objective evaluation.  ...  Medical image fusion technology has been widely used in clinical practice by doctors to better understand lesion regions through the fusion of multiparametric medical images.  ...  Image fusion based on deep learning has been widely used in multiparametric medical imaging [25] , infrared and visible imaging [26] , and remote sensing imaging [27] .  ... 
doi:10.1109/access.2021.3061078 fatcat:epnld57ngvab5cifdbnet6ffgm

Challenges in the Use of Artificial Intelligence for Prostate Cancer Diagnosis from Multiparametric Imaging Data

Daniele Corradini, Leonardo Brizi, Caterina Gaudiano, Lorenzo Bianchi, Emanuela Marcelli, Rita Golfieri, Riccardo Schiavina, Claudia Testa, Daniel Remondini
2021 Cancers  
AI includes methods such as Machine Learning and Deep learning techniques that have shown to be successful in classifying mp-MR images, with similar performances obtained by radiologists.  ...  In recent years, many aspects in the diagnosis of cancer have taken advantage of the use of Artificial Intelligence (AI) such as detection, segmentation of organs and/or lesions, and characterization.  ...  Here we follow the common framework for which AI includes methods such as Machine Learning and Deep Learning.  ... 
doi:10.3390/cancers13163944 fatcat:oxrznul5hnh4pnjyakkpgoxkn4
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