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A Fully-Automated Pipeline for Detection and Segmentation of Liver Lesions and Pathological Lymph Nodes [article]

Assaf Hoogi, John W. Lambert, Yefeng Zheng, Dorin Comaniciu, Daniel L. Rubin
2017 arXiv   pre-print
We propose a fully-automated method for accurate and robust detection and segmentation of potentially cancerous lesions found in the liver and in lymph nodes.  ...  Preliminary results under 10-fold cross validation show that for both the liver lesions and the lymph nodes, a total detection sensitivity of 0.53 and average Dice score of 0.71 ± 0.15 for segmentation  ...  Acknowledgments This work was supported in part by grants from the National Cancer Institute, National Institutes of Health, U01CA142555, 1U01CA190214, and 1U01CA187947.  ... 
arXiv:1703.06418v1 fatcat:nb26s3bz5ndmtj3xepvhsnkvee

Development of the Lymphatic System in the 4D XCAT Phantom [article]

Roberto Fedrigo
2021 arXiv   pre-print
Results: Lymph nodes can be scaled, stretched, and translated within the intuitive Rhinoceros interface, to allow for realistic simulation of different lymph node pathologies.  ...  It includes a complete set of organs, muscle, bone, soft tissue, while also accounting for age, sex, and body mass index (BMI), which allows phantom studies to be performed at a population scale.  ...  In any case, there is significant motivation to implement and assess semi-or fully-automated segmentation methods for use in a clinical setting such that reporting TMTV becomes a standard of care to better  ... 
arXiv:2107.11429v3 fatcat:n6symhxsuvakzaeos6d77qvssi

A Generalized Deep Learning Framework for Whole-Slide Image Segmentation and Analysis [article]

Mahendra Khened, Avinash Kori, Haran Rajkumar, Balaji Srinivasan, Ganapathy Krishnamurthi
2020 arXiv   pre-print
On CAMELYON16 test data (n=139) for the task of lesion detection, the FROC score achieved was 0.86 and in the CAMELYON17 test-data (n=500) for the task of pN-staging the Cohen's kappa score achieved was  ...  On PAIP test data (n=40) for the task of viable tumor segmentation, a Jaccard Index of 0.75 (third in the challenge) was achieved, and for viable tumor burden, a score of 0.633 was achieved (second in  ...  In this regard, an automated pipeline for lymph node metastases classification and pN-staging was developed.  ... 
arXiv:2001.00258v2 fatcat:cr4kxhu4pjdfxl3drmvuu6zjhy

A generalized deep learning framework for whole-slide image segmentation and analysis

Mahendra Khened, Avinash Kori, Haran Rajkumar, Ganapathy Krishnamurthi, Balaji Srinivasan
2021 Scientific Reports  
Automated segmentation of tumorous tissue helps in elevating the precision, speed, and reproducibility of research.  ...  , and liver cancer (PAIP).  ...  In this regard, an automated pipeline for lymph node metastases classification and pN-staging was developed.  ... 
doi:10.1038/s41598-021-90444-8 pmid:34078928 fatcat:xbg5bfa4arer3hyz2q5bonm7fy

Shape Detection In 2D Ultrasound Images [article]

Ruturaj Gole, Haixia Wu, Subho Ghose
2019 arXiv   pre-print
Our project aims to use Dual Path Networks (DPN) to segment and detect shapes in ultrasound images taken from 3D printed models of the liver.  ...  Ultrasound images are one of the most widely used techniques in clinical settings to analyze and detect different organs for study or diagnoses of diseases.  ...  of the segmented lymph nodes.  ... 
arXiv:1911.09863v1 fatcat:ek56tdhcavdcbo3ok5sjjofq4q

Front Matter: Volume 10134

2017 Medical Imaging 2017: Computer-Aided Diagnosis  
Utilization of CIDs allows articles to be fully citable as soon as they are published online, and connects the same identifier to all online and print versions of the publication.  ...  using a Base 36 numbering system employing both numerals and letters.  ...  segmentation using SLIC and interactive region merging 10134 3I Advancements in automated tissue segmentation pipeline for contrast-enhanced CT scans of adult and pediatric patients 10134 3J Texture  ... 
doi:10.1117/12.2277119 dblp:conf/micad/X17 fatcat:ika7pheqxngdxejyvkss4dkbv4

Artificial intelligence for assisting cancer diagnosis and treatment in the era of precision medicine

Zi-Hang Chen, Li Lin, Chen-Fei Wu, Chao-Feng Li, Rui-Hua Xu, Ying Sun
2021 Cancer Communications  
Deep learning (DL), a subfield of AI, is characterized by its ability to perform automated feature extraction and has great power in the assimilation and evaluation of large amounts of complicated data  ...  In this review, we introduced the general principle of AI, summarized major areas of its application for cancer diagnosis and treatment, and discussed its future directions and remaining challenges.  ...  They have been used for cancer lesion detection, recognition, segmentation and the classification of medical images [8] [9] [10] .  ... 
doi:10.1002/cac2.12215 pmid:34613667 pmcid:PMC8626610 fatcat:nt5z4icazfarhhensa7lyoy2e4

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

Model-Based Pancreas Segmentation in Portal Venous Phase Contrast-Enhanced CT Images

Matthias Hammon, Alexander Cavallaro, Marius Erdt, Peter Dankerl, Matthias Kirschner, Klaus Drechsler, Stefan Wesarg, Michael Uder, Rolf Janka
2013 Journal of digital imaging  
Reliable pancreatic segmentation is crucial for computeraided detection systems and an organ-specific decision support.  ...  The algorithmbased detection and segmentation yielded an average surface distance of 1.7 mm and an average overlap of 61.2 % compared with the reference standard.  ...  Parts of this research were done for Fraunhofer IDM@NTU, which is funded by the National Research Foundation (NRF) and managed through the multi-agency Interactive and Digital Media Programme Office (IDMPO  ... 
doi:10.1007/s10278-013-9586-7 pmid:23471751 pmcid:PMC3824921 fatcat:sswmoekzerfzrlxh5wuzic6jya

Recent Advances in Machine Learning Applied to Ultrasound Imaging

Monica Micucci, Antonio Iula
2022 Electronics  
The former, which covers the major part of the review, was analyzed by classifying studies according to the human organ investigated and the methodology (e.g., detection, segmentation, and/or classification  ...  ) adopted, while for the latter, some solutions to the detection/classification of material defects or particular patterns are reported.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/electronics11111800 fatcat:htw3q5kednhkbndgk7vw3tbvya

AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging: Towards Radiophenomics [article]

Fereshteh Yousefirizi, Pierre Decazes, Amine Amyar, Su Ruan, Babak Saboury, Arman Rahmim
2022 arXiv   pre-print
This work reviews AI-based techniques, with a special focus on oncological PET and PET/CT imaging, for different detection, classification, and prediction/prognosis tasks.  ...  Radiomics analysis has the potential to be utilized as a noninvasive technique for the accurate characterization of tumors to improve diagnosis and treatment monitoring.  ...  Acknowledgements This project was in part supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant RGPIN-2019-06467, and the Canadian Institutes of Health Research  ... 
arXiv:2110.10332v4 fatcat:vmpxhoolarbrve5ddyfn5umfim

Advances in Deep Learning-Based Medical Image Analysis

Xiaoqing Liu, Kunlun Gao, Bo Liu, Chengwei Pan, Kongming Liang, Lifeng Yan, Jiechao Ma, Fujin He, Shu Zhang, Siyuan Pan, Yizhou Yu
2021 Health Data Science  
With the booming growth of artificial intelligence (AI), especially the recent advancements of deep learning, utilizing advanced deep learning-based methods for medical image analysis has become an active  ...  This paper reviewed the recent progress of deep learning research in medical image analysis and clinical applications.  ...  Zhang et al. [80] built a fully automated, scalable, analysis pipeline for echocardio- gram interpretation, including view identification, cardiac chamber segmentation, quantification of structure and  ... 
doi:10.34133/2021/8786793 fatcat:d6nkb4yoxrcgni4y5owju5pnh4

Editorial Message from the Editor-in-Chief

João Manuel R. S. Tavares
2019 Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization  
compared four different loss functions for deep convolutional neural networks (CNNs) in the context of computer-aided abdominal and mediastinal lymph node detection and diagnosis (CAD) using CT images;  ...  described a fully automatic framework for kidney segmentation with convolutional networks in contrast-enhanced CT scans; 8) Xie et al. addressed automated cell counting and detection in microscopy images  ... 
doi:10.1080/21681163.2019.1591722 fatcat:wehmcoib6rdvjdcxsnmhkiksfm

ESGAR 2019 Book of Abstracts

2019 Insights into Imaging  
performed by expert readers and a fully automated algorithm, comprising both a machine learning-based liver segmentation and a 3D affine transformation network.  ...  We applied a fully automated registration algorithm to liver imaging studies to determine its impact on reader confidence and lesion colocalization.  ... 
doi:10.1186/s13244-019-0748-0 pmid:31165358 pmcid:PMC6548780 fatcat:te5vgmwwlzcw5ou5wz3vdpsoiu

Illustrative Visualization [article]

Ivan Viola, Meister E. Gröller, Markus Hadwiger, Katja Bühler, Bernhard Preim, David Ebert
2005 Eurographics State of the Art Reports  
To effectively convey the most important visual information there is a significant need for visual abstraction.  ...  Different stroke techniques, or brush properties express a particular level of abstraction.  ...  Acknowledgements The work presented in this publication is carried out as part of the ex vis ation project ( supported by the Austrian Science Fund (FWF) grant  ... 
doi:10.2312/egt.20051052 fatcat:gajqb72wvreovjxr3hc3zzetze
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