Study of morphological and textural features for classification of oral squamous cell carcinoma by traditional machine learning techniques-Reference-Cited by-同舟云学术

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Study of morphological and textural features for classification of oral squamous cell carcinoma by traditional machine learning techniques

Published:2020-10-07 Issue:6 Volume:3 Page:
ISSN:2573-8348
Container-title:Cancer Reports
language:en
Short-container-title:Cancer Reports

Author:

Rahman Tabassum Yesmin¹,Mahanta Lipi B.²^ORCID,Choudhury Hiten¹,Das Anup K.³,Sarma Jagannath D.⁴

Affiliation:

1. Department of Computer Science & IT Cotton University Guwahati India

2. Mathematical and Computational Sciences Division Institute of Advanced Study in Science and Technology Guwahati India

3. Pathology Arya Wellness Centre Guwahati India

4. Pathology Dr B. Borooah Cancer Institute Guwahati India

Publisher

Wiley

Subject

Cancer Research,Oncology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cnr2.1293

Reference55 articles.

1. Textural pattern classification for oral squamous cell carcinoma

2. Computer-aided evaluation of neuroblastoma on whole-slide histology images: Classifying grade of neuroblastic differentiation

3. Image segmentation through combined methods: Watershed transform, unsupervised distance learning and Normalized Cut

4. Early prognosis of metastasis risk in inflammatory breast cancer by texture analysis of tumour microscopic images

5. Texture analysis of CT images in the characterization of oral cancers involving buccal mucosa

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