A Multidimensional Choledoch Database and Benchmarks for Cholangiocarcinoma Diagnosis

Histopathological examination is very important for diseases diagnosis and treatment. With the development of artificial intelligence, more and more pathological databases have been reported for histopathological diagnosis because database is quite crucial for the validation and testing of feature extraction, statistical analysis and deep learning algorithms. However, most of these databases are either gray images or RGB color images of tissue sections contain limited information of samples which limited the performance of most current deep learning algorithms. There are few publicly available pathological databases that include more than two modalities for the same subject. This paper introduces a database for both microscopy hyperspectral and color images of cholangiocarcinoma, including 880 scenes from 174 individuals, among which 689 scenes are samples with part of cancer areas, 49 scenes full of cancer areas, and 142 scenes without cancer areas. In addition, all cancer areas have been precisely labeled by experienced pathologists. The contributions of this work: a) A comprehensive and up-to-date review on pathological imaging systems and databases; b) Detailed description of the proposed the multidimensional Choledoch Database and login method; c) The multidimensional Choledoch Database has been published and can be downloaded after registration and made an entry on the website.

[1]  Hongjun Wang,et al.  Tongue Tumor Detection in Medical Hyperspectral Images , 2011, Sensors.

[2]  John D. Pfeifer,et al.  Review of the current state of whole slide imaging in pathology , 2011, Journal of pathology informatics.

[3]  B F Boyce,et al.  An update on the validation of whole slide imaging systems following FDA approval of a system for a routine pathology diagnostic service in the United States , 2017, Biotechnic & histochemistry : official publication of the Biological Stain Commission.

[4]  Kristine A. Erps,et al.  Overview of telepathology, virtual microscopy, and whole slide imaging: prospects for the future. , 2009, Human pathology.

[5]  Shaimaa Al-Janabi,et al.  Whole slide images as a platform for initial diagnostics in histopathology in a medium-sized routine laboratory , 2012, Journal of Clinical Pathology.

[6]  Dongrong Xu,et al.  AOTF based molecular hyperspectral imaging system and its applications on nerve morphometry. , 2013, Applied optics.

[7]  Yukako Yagi,et al.  Use of whole slide imaging in surgical pathology quality assurance: design and pilot validation studies. , 2006, Human pathology.

[8]  Gustavo Marrero Callicó,et al.  Hyperspectral database of pathological in-vitro human brain samples to detect carcinogenic tissues , 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

[9]  Zheng Yuquan.  Precise spectral calibration for hyperspectral imager , 2010 .

[10]  Nasir M. Rajpoot,et al.  Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images , 2016, IEEE Trans. Medical Imaging.

[11]  Nigam H. Shah,et al.  The Stanford Tissue Microarray Database , 2007, Nucleic Acids Res..

[12]  R. Dunstan,et al.  The Use of Immunohistochemistry for Biomarker Assessment—Can It Compete with Other Technologies? , 2011, Toxicologic pathology.

[13]  Luiz Eduardo Soares de Oliveira,et al.  A Dataset for Breast Cancer Histopathological Image Classification , 2016, IEEE Transactions on Biomedical Engineering.

[14]  Oscar Déniz,et al.  An automated system for whole microscopic image acquisition and analysis , 2014, Microscopy research and technique.

[15]  Navid Farahani,et al.  whole slide imaging in pathology: advantages, limitations, and emerging perspectives , 2015 .

[16]  Toby C. Cornish,et al.  Whole-slide Imaging: Routine Pathologic Diagnosis , 2012, Advances in anatomic pathology.

[17]  Marios Anthimopoulos,et al.  Semantic Segmentation of Pathological Lung Tissue With Dilated Fully Convolutional Networks , 2018, IEEE Journal of Biomedical and Health Informatics.

[18]  Shohreh Kasaei,et al.  Benign and malignant breast tumors classification based on region growing and CNN segmentation , 2015, Expert Syst. Appl..

[19]  Dongrong Xu,et al.  Review of spectral imaging technology in biomedical engineering: achievements and challenges , 2013, Journal of biomedical optics.

[20]  Jin-Chern Chiou,et al.  Separating spectral mixtures in hyperspectral image data using independent component analysis: validation with oral cancer tissue sections , 2013, Journal of biomedical optics.

[21]  Nicholas Ayache,et al.  Model-Based Generation of Large Databases of Cardiac Images: Synthesis of Pathological Cine MR Sequences From Real Healthy Cases , 2018, IEEE Transactions on Medical Imaging.

[22]  Gautam Majumdar,et al.  Designing of Ground-Truth-Annotated DBT-TU-JU Breast Thermogram Database Toward Early Abnormality Prediction , 2018, IEEE Journal of Biomedical and Health Informatics.

[23]  Francesco Bianconi,et al.  Multi-class texture analysis in colorectal cancer histology , 2016, Scientific Reports.

[24]  Yassine Khazri,et al.  Improved Algorithm for Pathological and Normal Voices Identification , 2017 .

[25]  J. D. Webster,et al.  Whole-Slide Imaging and Automated Image Analysis , 2014, Veterinary pathology.

[26]  A. Evans,et al.  Implementation of Whole Slide Imaging for Clinical Purposes: Issues to Consider From the Perspective of Early Adopters. , 2017, Archives of pathology & laboratory medicine.

[27]  Walter H Henricks,et al.  Validation of whole slide imaging for primary diagnosis in surgical pathology. , 2013, Archives of pathology & laboratory medicine.

[28]  Surabhi Bhargava,et al.  A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology , 2017, IEEE Transactions on Medical Imaging.

[29]  Rodney Davis,et al.  Survival outcomes of organ sparing surgery, partial penectomy, and total penectomy in pathological T1/T2 penile cancer: Report from the National Cancer Data Base. , 2017, Urologic oncology.

[30]  LIANG Qiao-kang,et al.  Feasibility of deep learning image-based segmentation algorithm in pathological section of gastric cancer , 2018 .

[31]  C. Hutter,et al.  The Cancer Genome Atlas: Creating Lasting Value beyond Its Data , 2018, Cell.

[32]  Guang-Zhong Yang,et al.  Spatio-spectral classification of hyperspectral images for brain cancer detection during surgical operations , 2018, PloS one.

[33]  Hong Yan,et al.  A Novel Vessel Segmentation Algorithm for Pathological Retina Images Based on the Divergence of Vector Fields , 2008, IEEE Transactions on Medical Imaging.

[34]  Heng Huang,et al.  Panoptic Segmentation with an End-to-End Cell R-CNN for Pathology Image Analysis , 2018, MICCAI.

[35]  Dr. P. Suresh,et al.  SVM BASED LUNG TUMOR SEGMENTATION USING OTSU’S THRESHOLDING , 2016 .

[36]  Yasodha Natkunam,et al.  Characterization of D-Cyclin Proteins in Hematolymphoid Neoplasms: Lack of Specificity of Cyclins D2 and D3 Expression in Lymphoma Subtypes , 2009, Modern Pathology.

[37]  T. Ramakrishnan,et al.  A professional estimate on the computed tomography brain tumor images using SVM-SMO for classification and MRG-GWO for segmentation , 2017, Pattern Recognit. Lett..

[38]  Andrew Evans,et al.  Digital imaging in pathology: whole-slide imaging and beyond. , 2013, Annual review of pathology.

[39]  Giuseppe De Pietro,et al.  A new database of healthy and pathological voices , 2018, Comput. Electr. Eng..

[40]  Xiabi Liu,et al.  The LISS—A Public Database of Common Imaging Signs of Lung Diseases for Computer-Aided Detection and Diagnosis Research and Medical Education , 2015, IEEE Transactions on Biomedical Engineering.

[41]  S E Humphries,et al.  Low-density lipoprotein receptor gene (LDLR) world-wide website in familial hypercholesterolaemia: update, new features and mutation analysis. , 2001, Atherosclerosis.

[42]  Luma V. Halig,et al.  Hyperspectral imaging and quantitative analysis for prostate cancer detection. , 2012, Journal of biomedical optics.

[43]  Andrew C. R. Martin,et al.  Low‐Density Lipoprotein Receptor Gene Familial Hypercholesterolemia Variant Database: Update and Pathological Assessment , 2012, Annals of human genetics.

[44]  Dustin A. Bruening,et al.  Automated event detection algorithms in pathological gait. , 2014, Gait & posture.

[45]  Guang-Zhong Yang,et al.  In-Vivo Hyperspectral Human Brain Image Database for Brain Cancer Detection , 2019, IEEE Access.

[46]  Feng Nianlun.  Microscopic Image Analysis and Recognition on Pathological Cells , 2009 .

[47]  Min Zhang,et al.  A prior feature SVM-MRF based method for mouse brain segmentation , 2012, NeuroImage.

[48]  Dirk J Gouma,et al.  Impact of centralization of pancreatoduodenectomy on reported radical resections rates in a nationwide pathology database. , 2015, HPB : the official journal of the International Hepato Pancreato Biliary Association.

[49]  Alexis B. Carter,et al.  Validating whole slide imaging for diagnostic purposes in pathology: guideline from the College of American Pathologists Pathology and Laboratory Quality Center. , 2013, Archives of pathology & laboratory medicine.