Zohaib Salahuddin

About Zohaib Salahuddin

Zohaib Salahuddin, With an exceptional h-index of 6 and a recent h-index of 6 (since 2020), a distinguished researcher at Universiteit Maastricht, specializes in the field of Deep Learning, Medical Image Analysis.

His recent articles reflect a diverse array of research interests and contributions to the field:

Development of Clinical Radiomics-Based Models to Predict Survival Outcome in Pancreatic Ductal Adenocarcinoma: A Multicenter Retrospective Study

An Interpretable Radiomics Model Based on Two-Dimensional Shear Wave Elastography for Predicting Symptomatic Post-Hepatectomy Liver Failure in Patients with Hepatocellular …

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Precision-medicine-toolbox: An open-source python package for the quantitative medical image analysis

From Head and Neck Tumour and Lymph Node Segmentation to Survival Prediction on PET/CT: An End-to-End Framework Featuring Uncertainty, Fairness, and Multi-Region Multi-Modal …

UR-CarA-Net: a cascaded framework with uncertainty regularization for automated segmentation of carotid arteries on black blood MR images

From the clinic: A survey on trustworthy AI in breast cancer*

HNT-AI: an automatic segmentation framework for head and neck primary tumors and lymph nodes in FDG-PET/CT images

Zohaib Salahuddin Information

University

Position

PhD Student

Citations(all)

357

Citations(since 2020)

356

Cited By

2

hIndex(all)

6

hIndex(since 2020)

6

i10Index(all)

5

i10Index(since 2020)

5

Email

University Profile Page

Google Scholar

Zohaib Salahuddin Skills & Research Interests

Deep Learning

Medical Image Analysis

Top articles of Zohaib Salahuddin

Development of Clinical Radiomics-Based Models to Predict Survival Outcome in Pancreatic Ductal Adenocarcinoma: A Multicenter Retrospective Study

Diagnostics

2024/3/28

Zohaib Salahuddin
Zohaib Salahuddin

H-Index: 1

Philippe Lambin
Philippe Lambin

H-Index: 68

An Interpretable Radiomics Model Based on Two-Dimensional Shear Wave Elastography for Predicting Symptomatic Post-Hepatectomy Liver Failure in Patients with Hepatocellular …

Cancers

2023/11/6

Precision-medicine-toolbox: An open-source python package for the quantitative medical image analysis

Software Impacts

2023/5/1

From Head and Neck Tumour and Lymph Node Segmentation to Survival Prediction on PET/CT: An End-to-End Framework Featuring Uncertainty, Fairness, and Multi-Region Multi-Modal …

Cancers

2023/3/23

UR-CarA-Net: a cascaded framework with uncertainty regularization for automated segmentation of carotid arteries on black blood MR images

IEEE Access

2023/3/16

From the clinic: A survey on trustworthy AI in breast cancer*

2023/12/7

HNT-AI: an automatic segmentation framework for head and neck primary tumors and lymph nodes in FDG-PET/CT images

Head and Neck Tumor Segmentation and Outcome Prediction: Third Challenge, HECKTOR 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings

2023/3/17

Diagnosis of idiopathic pulmonary fibrosis in high-resolution computed tomography scans using a combination of handcrafted radiomics and deep learning

Frontiers in medicine

2022/6/23

CT reconstruction kernels and the effect of pre-and post-processing on the reproducibility of handcrafted radiomic features

Journal of Personalized Medicine

2022/3/31

MaasPenn radiomics reproducibility score: A novel quantitative measure for evaluating the reproducibility of CT-based handcrafted radiomic features

Cancers

2022/3/22

Transparency of deep neural networks for medical image analysis: A review of interpretability methods

2022/1/1

Zohaib Salahuddin
Zohaib Salahuddin

H-Index: 1

Philippe Lambin
Philippe Lambin

H-Index: 68

FUTURE-AI: guiding principles and consensus recommendations for trustworthy artificial intelligence in medical imaging

arXiv preprint arXiv:2109.09658

2021/9/20

Making radiomics more reproducible across scanner and imaging protocol variations: a review of harmonization methods

2021/9

Multi-resolution 3d convolutional neural networks for automatic coronary centerline extraction in cardiac CT angiography scans

arXiv preprint arXiv:1805.12254

2018/5

Leveraging slic superpixel segmentation and cascaded ensemble svm for fully automated mass detection in mammograms

arXiv preprint arXiv:2010.10340

2020/10/20

Zohaib Salahuddin
Zohaib Salahuddin

H-Index: 1

See List of Professors in Zohaib Salahuddin University(Universiteit Maastricht)

Co-Authors

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