Rabby, Saha, Abujar, Rahman. One Model Multiple Insights: CNNs for Medical Image Classification
IEEE International Conference on Big Data, 2024 · First author
Research Scientist · PhD, Computer Science
University of Alabama at Birmingham — CLAIR & KDDM Lab
My research asks whether vision systems can recognize missing branches, broken connections, and false junctions from image evidence and their own predictions, without reference masks at inference time. I study when targeted correction improves structural reliability over uniform refinement, alongside supporting questions about multimodal evidence and efficient inference.
Thin-Structure Segmentation · Minority-Class Segmentation · Deployable AI (MLOps)
My work sits at the intersection of representation learning for thin, elongated, and minority-class structures and systems that are deployed and validated in the field — clinical and industrial, not just benchmarked.
The current thread began with lightweight, multicenter COPD detection and now focuses on 3D pulmonary fissure segmentation and a fissure-integrity score for studying completeness and connectivity across the lung.
As a Research Scientist at UAB, this line is active through 3D pulmonary fissure segmentation and an algorithmic fissure-integrity score. The program extends from it in three directions:
Foundations. Earlier work in low-resource language processing and document understanding — including Bangla OCR, handwriting, and sign-language datasets — developed the dataset-design and rare-class modeling skills that support this program.
Academic appointments, teaching, and selected industry leadership
50 peer-reviewed publications, including 16 first-author papers. Full record on Google Scholar →
IEEE International Conference on Big Data, 2024 · First author
Respiratory Medicine (Elsevier), 2025
IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2026 · First author
A directional encoder–decoder for pulmonary fissure segmentation. It achieved Dice 0.873 and median HD95 0.72 mm on 50 COPDGene CT scans evaluated with subject-level five-fold cross-validation; the model has approximately 5.1 million parameters. Accepted at IEEE BIBM 2026; proceedings forthcoming.
IEEE International Conference on Information Reuse and Integration (IRI), 2025 · First author
Edge-Guided Attention for minority-class crack segmentation, plus the dCrack61K benchmark (61,943 images, 36 sources, 2,000+ corrected annotations). Cross-domain transfer: F1 0.8251 on CHASE_DB1 retinal vessels without vessel-specific training.
@inproceedings{rabby2025dcrack,
title = {dCrack: Enhancing Fine-Grained Crack Segmentation with Edge-Guided Attention},
author = {Rabby, Shahariar and Zhang, Chengcui},
booktitle = {IEEE International Conference on Information Reuse and Integration (IRI)},
year = {2025}
}
EACL Industry Track, pp. 278–286, 2026
IEEE/CVF WACV Workshops, 2024 · First author
IEEE International Conference on Machine Learning and Applications (ICMLA), 2021 · First author
EMNLP Industry Track, 2023 · Co-first author
RTIP2R, Springer, 2018 · First author
A large-scale Bangla handwritten character dataset: 673K instances across 242 classes. A common baseline dataset for Bangla OCR research.
medRxiv preprint · under review at The Lancet Digital Health · First & corresponding author
A 10.6M-parameter 3D CNN evaluated on 13,043 COPDGene CT scans from 21 centers using participant-level train/test separation. AUC was 0.92 for standard-dose and 0.88 for low-dose scans; external AUC was 0.92 on SPIROMICS and 0.82 on NLST.
Manuscript under review · First author
Across four benchmarks, mean [email protected] was 0.8250. On Crack500, [email protected] was 0.7481 and clDice was 0.8202. The model has 5.634M parameters and 9.326 GFLOPs (48.6% below SCSegamba); inference reached 75.35 FPS on NVIDIA A6000 and 4.711 FPS at 256×256 or 0.970 FPS at 512×512 on Raspberry Pi 5.
50 accepted or published peer-reviewed papers (including 16 first-author papers), plus 3 manuscripts/preprints and 1 ATS conference abstract. Google Scholar ↗
Dissertation: Precise Segmentation of Thin, Elongated, and Underrepresented Structures. Advisor: Dr. Chengcui Zhang. CS Outstanding PhD Student Award, 2026.
Coursework: Machine Learning, Deep Learning, Data Science, Cloud Computing, Algorithms.
Thesis: Ekush: Bangla Handwritten Character Data Repository for NLP Research.
Medical imaging AI, document understanding, or deployable ML.