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Literature DB >> 18517267

Computer-assisted grading of neuroblastic differentiation.

Jun Kong, Olcay Sertel, Kim L Boyer, Joel H Saltz, Metin N Gurcan, Hiroyuki Shimada.

Abstract

Mesh：

Year: 2008 PMID： 18517267 DOI： 10.5858/2008-132-903-CGOND

Source DB: PubMed Journal: Arch Pathol Lab Med ISSN： 0003-9985 Impact factor: 5.534

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7 in total

1. Digital pathology image analysis: opportunities and challenges.

Authors: Anant Madabhushi
Journal: Imaging Med Date: 2009

2. Integrated morphologic analysis for the identification and characterization of disease subtypes.

Authors: Lee A D Cooper; Jun Kong; David A Gutman; Fusheng Wang; Jingjing Gao; Christina Appin; Sharath Cholleti; Tony Pan; Ashish Sharma; Lisa Scarpace; Tom Mikkelsen; Tahsin Kurc; Carlos S Moreno; Daniel J Brat; Joel H Saltz
Journal: J Am Med Inform Assoc Date: 2012-01-24 Impact factor: 4.497

3. Scalable analysis of Big pathology image data cohorts using efficient methods and high-performance computing strategies.

Authors: Tahsin Kurc; Xin Qi; Daihou Wang; Fusheng Wang; George Teodoro; Lee Cooper; Michael Nalisnik; Lin Yang; Joel Saltz; David J Foran
Journal: BMC Bioinformatics Date: 2015-12-01 Impact factor: 3.169

4. Extracellular matrix composition defines an ultra-high-risk group of neuroblastoma within the high-risk patient cohort.

Authors: Irene Tadeo; Ana P Berbegall; Victoria Castel; Purificación García-Miguel; Robert Callaghan; Sven Påhlman; Samuel Navarro; Rosa Noguera
Journal: Br J Cancer Date: 2016-07-14 Impact factor: 7.640

Computer-assisted grading of neuroblastic differentiation.

1. Digital pathology image analysis: opportunities and challenges.

2. Integrated morphologic analysis for the identification and characterization of disease subtypes.

3. Scalable analysis of Big pathology image data cohorts using efficient methods and high-performance computing strategies.

4. Extracellular matrix composition defines an ultra-high-risk group of neuroblastoma within the high-risk patient cohort.

5. Predicting cancer outcomes from histology and genomics using convolutional networks.

6. Interactive phenotyping of large-scale histology imaging data with HistomicsML.

7. A Methodology for Texture Feature-based Quality Assessment in Nucleus Segmentation of Histopathology Image.