Author

April Khademi

St. Michael's HospitalORCID 0000-0002-4932-0385Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:imaging· 3 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Abel G. Silva-Filho· 1 shared Abishika SivanandarajahiD· 1 shared Adam GibicariD· 1 shared Alan R. MoodyiD· 1 shared Amirreza MahbodiD· 1 shared Anne KerbratiD· 1 shared Audrey Istace· 1 shared Baptiste LaurentiD· 1 shared

Activity by Year

2018-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 22 mutual co-author links

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1 shared paperNeuroscience

Abel G. Silva-Filho

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Author profile →

3 papers

Recent·Most cited

White Matter Lesion Asymmetry and Carotid Intraplaque Hemorrhage: A Novel Imaging Phenotype for Stroke Risk in Older Men

Nicholas Simard, Faraz Honarvar, Joshua Noronha, Adam Gibicar, Pascal N. Tyrrell, Alan R. Moody, Maria Natasha Rajah, Sandra E. Black, Pejman Jabehdar Maralani, April Khademi

This study identifies carotid intraplaque hemorrhage as an independent predictor of asymmetric white matter lesion pathology in older men, highlighting a novel imaging marker for stroke risk.

bioRxiv · Jan 30, 2026 · PreprintNeuroscience

piNET: An Automated Proliferation Index Calculator Framework for Ki67 Breast Cancer Images

Rokshana Stephny Geread, Abishika Sivanandarajah, Emily Rita Brouwer, Geoffrey A. Wood, Dimitrios Androutsos, Hala Faragalla, April Khademi

piNET is a deep learning framework for Ki67 proliferation index calculation in breast cancer images, achieving high accuracy and correlation across diverse datasets.

Cancers · Dec 22, 2020Peer-reviewedBioinformatics

Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure

Olivier Commowick, Audrey Istace, Michaël Kain, Baptiste Laurent, Florent Leray, Mathieu Simon, Sorina Camarasu-Pop, Pascal Girard, Roxana Améli, Jean‐Christophe Ferré, Anne Kerbrat, Thomas Tourdias, Frédéric Cervenansky, Tristan Glatard, Jérémy Beaumont, , Christian Barillot

This paper evaluates MS lesion segmentation algorithms using a new open-science infrastructure, finding that automatic methods lag behind human experts in detection and delineation.

Scientific Reports · Sep 6, 2018Peer-reviewedNeuroscience