Search Results - "Cruz-Roa AA"

Improved DeepMitosisNet framework for detection of mitosis in histopathology images.

Authors: B, Lakshmanan S, Anand P.S, Vivek Raja et al.

Source: Multimedia Tools & Applications; Apr2024, Vol. 83 Issue 14, p43303-43324, 22p

Pathology-informed Generative Adversarial Network Augmentation Improves Classification of Peripheral Nerve Sheath Tumors by Modeling Morphological Variability: A Pilot Investigation.

Authors: Santos GCD Silva HVLB Araújo ALD et al.

Source: Head and neck pathology [Head Neck Pathol] 2026 Jun 26; Vol. 20 (1). Date of Electronic Publication: 2026 Jun 26.

Publication Type: Journal Article

Journal Info: Publisher: Country of Publication: United States NLM ID: 101304010 Publication Model: Electronic Cited Medium: Internet ISSN: 1936-0568 (Electronic) Linking ISSN: 1936055X NLM ISO Abbreviation: Head Neck Pathol Subsets: MEDLINE

Towards Diagnosis of Autoimmune Blistering Skin Diseases Using Deep Neural Network.

Authors: Singh, Manbir Singh, Maninder De, Dipankar et al.

Source: Archives of Computational Methods in Engineering; Jul2023, Vol. 30 Issue 6, p3529-3557, 29p

Artificial intelligence in Dermatopathology.

Authors: Jartarkar, Shishira R. Cockerell, Clay J. Patil, Anant et al.

Source: Journal of Cosmetic Dermatology. Apr2023, Vol. 22 Issue 4, p1163-1167. 5p.

AM-UNet: automated mini 3D end-to-end U-net based network for brain claustrum segmentation.

Authors: Albishri, Ahmed Awad Shah, Syed Jawad Hussain Kang, Seung Suk et al.

Source: Multimedia Tools & Applications; Oct2022, Vol. 81 Issue 25, p36171-36194, 24p

E-Tanh: a novel activation function for image processing neural network models.

Authors: Kalaiselvi, T. Padmapriya, S. T. Somasundaram, K. et al.

Source: Neural Computing & Applications; Oct2022, Vol. 34 Issue 19, p16563-16575, 13p

Multiclass skin lesion classification and localziation from dermoscopic images using a novel network-level fused deep architecture and explainable artificial intelligence.

Authors: Arshad, Mehak Khan, Muhammad Attique Almujally, Nouf Abdullah et al.

Source: BMC Medical Informatics & Decision Making. 7/1/2025, Vol. 25 Issue 1, p1-22. 22p.

Outbreak COVID-19 in Medical Image Processing Using Deep Learning: A State-of-the-Art Review.

Authors: Kaur, Jaspreet Kaur, Prabhpreet

Source: Archives of Computational Methods in Engineering; Jun2022, Vol. 29 Issue 4, p2351-2382, 32p

Literature review: efficient deep neural networks techniques for medical image analysis.

Authors: Abdou, Mohamed A.¹, mabdou@srtacity.sci.eg

Source: Neural Computing & Applications; 4/15/2022, Vol. 34 Issue 8, p5791-5812, 22p

Artificial intelligence significantly improves the diagnostic accuracy of deep myxoid soft tissue lesions in histology.

Authors: Yeung, Maximus C. F. Cheng, Ivy S. Y.

Source: Scientific Reports. 4/28/2022, Vol. 12 Issue 1, p1-9. 9p.

Deep learning techniques for detecting preneoplastic and neoplastic lesions in human colorectal histological images.

Authors: Sena, Paola Fioresi, Rita Faglioni, Francesco et al.

Source: Oncology Letters. Dec2019, Vol. 18 Issue 6, p6101-6107. 7p.

Real-world data: a brief review of the methods, applications, challenges and opportunities.

Authors: Liu, Fang Demosthenes, Panagiotakos

Source: BMC Medical Research Methodology. 11/5/2022, Vol. 22 Issue 1, p1-10. 10p.

Microscopic nuclei classification, segmentation, and detection with improved deep convolutional neural networks (DCNN).

Authors: Alom, Zahangir Asari, Vijayan K. Parwani, Anil et al.

Source: Diagnostic Pathology. 4/19/2022, Vol. 17 Issue 1, p1-17. 17p.

Supervised machine learning for automated classification of human Wharton's Jelly cells and mechanosensory hair cells.

Authors: Kothapalli, Abihith Staecker, Hinrich Mellott, Adam J.

Source: PLoS ONE. 1/8/2021, Vol. 16 Issue 1, p1-11. 11p.

Systematic review of machine learning for diagnosis and prognosis in dermatology.

Authors: Thomsen, Kenneth Iversen, Lars Titlestad, Therese Louise et al.

Source: Journal of Dermatological Treatment. Aug2020, Vol. 31 Issue 5, p496-510. 15p.

Comparison of Shallow and Deep Learning Methods on Classifying the Regional Pattern of Diffuse Lung Disease.

Authors: Kim, Guk Bae Jung, Kyu-Hwan Lee, Yeha et al.

Source: Journal of Digital Imaging; Aug2018, Vol. 31 Issue 4, p415-424, 10p, 2 Color Photographs, 3 Diagrams, 5 Charts

Deep learning in bioinformatics.

Authors: Seonwoo Min Byunghan Lee Sungroh Yoon

Source: Briefings in Bioinformatics. Sep2017, Vol. 18 Issue 5, p851-869. 19p.

Whole slide imaging in pathology: what is holding us back?

Authors: Feldman, Michael D.¹ feldmanm@mail.med.upenn.edu

Source: Pathology & Laboratory Medicine International. 2015, Vol. 7, p35-38. 4p.

A Computer-Aided Decision Support System for Detection and Localization of Cutaneous Vasculature in Dermoscopy Images Via Deep Feature Learning.

Authors: Kharazmi, Pegah Zheng, Jiannan Lui, Harvey et al.

Source: Journal of Medical Systems. Feb2018, Vol. 42 Issue 2, p1-12. 12p.

Improving prediction of phenotypic drug response on cancer cell lines using deep convolutional network.

Authors: Liu, Pengfei Li, Hongjian Li, Shuai et al.

Source: BMC Bioinformatics. 7/29/2019, Vol. 20 Issue 1, pN.PAG-N.PAG. 1p. 2 Color Photographs, 1 Chart, 5 Graphs.