collaborators

5 papers

cs.CV2026

Segmentation and Classification of Pap Smear Images for Cervical Cancer Detection Using Deep Learning

Nisreen Albzour, Sarah S. Lam

Cervical cancer remains a significant global health concern and a leading cause of cancer-related deaths among women. Early detection through Pap smear tests is essential to reduce…

cs.CV2026

Reliability-Aware Ensemble Classification Under Class Imbalance: A Calibration Study on Liquid-Based Cervical Cytology

Nisreen Albzour, Sarah S. Lam

Cervical cytology classification models are typically evaluated on curated, class-balanced benchmarks, but real-world liquid-based cytology (LBC) collections are often small and cl…

cs.CV2026

Reliability-Aware CT-MRI Registration: A Quality Engineering Framework with Stability Analysis and Risk Classification

Nisreen Albzour

Multimodal CT-MRI registration is central to image-guided radiotherapy, surgical navigation, and diagnostic workflows, but most pipelines report only aggregate quality metrics with…

eess.IV2026

A Leakage-Aware Comparative Benchmark of Machine Learning, Deep Learning, and Transformer Models for Reliable Leukemia Detection

Nisreen Albzour

Automated classification of acute lymphoblastic leukemia (ALL) from peripheral blood smear images has often reported near-perfect performance on the C-NMC 2019 dataset. We show tha…

cs.CV2026

Systematic Evaluation of Vision Transformers for Automated Cervical Cancer Classification: Optimization, Statistical Validation, and Clinical Interpretability

Nisreen Albzour, Sarah S. Lam

Manual Pap smear analysis for cervical cancer screening is limited by inter-observer variability, time constraints, and restricted expert availability. Although convolutional neura…