Journal Articles & Conference Papers

D. Jha et al., “ Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 Challenges ,” Medical Image Analysis, 2024.

D. Jha, “ Machine Learning-based Classification, Detection, and Segmentation of Medical Images ,” PhD Thesis, 2022.

D. Jha et al., “ A Comprehensive analysis of classification methods in gastrointestinal endoscopy imaging ,” Medical Image Analysis, vol. 70, 2021.

D. Jha et al., “ A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time Augmentation ,” IEEE Journal of Biomedical and Health Informatics, 2021.

D. Jha et al., “ Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning ,” IEEE Journal of Biomedical and Health Informatics, 2021.

D. Jha et al., “ PolypGen: A multi-center polyp detection and segmentation dataset for generalisability assessment ,” Nature Scientific Data, 2023.

H. Borgli*, V. Thambawita*, P. Smedsrud*, S. Hicks*, D. Jha*, S. Eskeland, et al., “ Hyper-Kvasir: A Comprehensive Multi-Class Image and Video Dataset for Gastrointestinal Endoscopy ,” Nature Scientific Data [Contributed equally], 2020.

P. Smedsrud*, H. Gjestang*, O. Nedrejord*, E. Næss*, V. Thambawita*, S. Hicks*, H. Borgli*, D. Jha*, et al., “ Kvasir-Capsule, a video capsule endoscopy dataset ,” Nature Scientific Data [equally contributed], 2021.

N. Tomar, D. Jha et al., “ FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation ,” IEEE Transactions on Neural Networks and Learning Systems, 2022.

A. Srivastava, D. Jha et al., “ MSRF-Net: A Multi-Scale Residual Fusion Network for Biomedical Image Segmentation ,” IEEE Journal of Biomedical and Health Informatics, 2022.

T. Ross, A. Reinke, D. Jha et al., “ Comparative validation of multi-instance instrument segmentation in endoscopy: results of the ROBUST-MIS 2019 Challenge ,” Medical Image Analysis, vol. 70, 2021.

D. Jha et al., “ Diagnosis of Alzheimer’s Disease Using Dual-Tree Complex Wavelet Transform, PCA, and Feed-Forward Neural Network ,” Journal of Healthcare Engineering, 2017.

V. Thambawita, D. Jha et al., “ An Extensive Study on Cross-Dataset Bias and Evaluation Metrics Interpretation for Machine Learning Applied to Gastrointestinal Tract Abnormality Classification ,” ACM Transactions on Computing for Healthcare, vol. 1, no. 3, 2021.

R. Khadka, D. Jha et al., “ Meta-learning with implicit gradients in a few-shot setting for medical image segmentation ,” Computers in Biology and Medicine, 2022.

D. Jha et al., “ DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation,” CBMS, 2020.

D. Jha et al., “ Kvasir-SEG: A segmented polyp dataset,” IEEE ISM, 2019.

D. Jha et al., “ ResUNet++: An advanced architecture for medical image segmentation,” IEEE ISM, 2019.

D. Jha et al., “ NanoNet: Real-Time Polyp Segmentation in Video Capsule Endoscopy and Colonoscopy,” IEEE CBMS.

D. Jha et al., “ LightLayers: Parameter-Efficient Dense and Convolutional Layers for Image Classification,” PDCAT-PAAP, 2020.

S. A. Hicks, D. Jha, V. Thambawita, P. Halvorsen and M. Riegler, “ The EndoTect 2020 Challenge: Evaluation and Comparison of Classification, Segmentation and Inference Time for Endoscopy,” ICPR Workshop, 2020.

G.-P. Ji, Y.-C. Chou, D.-P. Fan, G. Chen, H. Fu, D. Jha, L. Shao, “ Progressively Normalized Self-Attention Network for Video Polyp Segmentation,” MICCAI, 2021.

N. K Tomar, D. Jha, U. Bagci, Sharib Ali, “ Text-guided attention for improved polyp segmentation,” MICCAI, 2022.

D. Jha et al., “ Exploring Deep Learning Methods for Real-Time Surgical Instrument Segmentation in Laparoscopy,” IEEE BHI, 2021.

N. K. Tomar, A. Shergill, B. Rieders, U. Bagci, & D. Jha, “ TransResU-Net: Transformer-based ResU-Net for Real-Time Colonoscopy Polyp Segmentation,” IEEE BHI, 2022.

D. Jha et al., “ GastroVision: A Multi-class Endoscopy Image Dataset for Computer-Aided GI Disease Detection,” ICML ML4MHD Workshop, 2023.

D. Jha et al., “ CT Liver Segmentation via PVT-based Encoding and Refined Decoding,” ISBI, 2024.

D. Jhaetal., “ TransNetR: Transformer-based Residual Network for Polyp Segmentation with Multi-Center Out-of-Distribution Testing,” MIDL, 2023.