Adam Mushtak

According to our database, Adam Mushtak authored at least 13 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

A Two-Stage Deep Learning Framework for Segmentation of Ten Gastrointestinal Organs from Coronal MR Enterography.

Ashiqur Rahman, Md. Abu Sayed, Md Sharjis Ibne Wadud, Md. Abu Asad Al-Hafiz, Adam Mushtak, Muhammad E. H. Chowdhury

CoRR, April, 2026

Tracing 3D Anatomy in 2D Strokes: A Multi-Stage Projection Driven Approach to Cervical Spine Fracture Identification.

Fabi Nahian Madhurja, Rusab Sarmun, Muhammad E. H. Chowdhury, Adam Mushtak, Israa Al-Hashimi, Sohaib Bassam Zoghoul

CoRR, January, 2026

2025

An Anatomy Aware Hybrid Deep Learning Framework for Lung Cancer Tumor Stage Classification.

Saniah Kayenat Chowdhury, Rusab Sarmun, Muhammad E. H. Chowdhury, Sohaib Bassam Zoghoul, Israa Al-Hashimi, Adam Mushtak, Amith Khandakar

CoRR, November, 2025

Improving pediatric trauma care: an automated system for wrist trauma detection using GELAN.

Promit Basak, Adam Mushtak, Mohamed Ouda, Sadia Farhana Nobi, Anwarul Hasan, Muhammad E. H. Chowdhury

Neural Comput. Appl., October, 2025

Multiclass ensemble framework for enhanced prostate gland Segmentation: Integrating Self-ONN decoders with EfficientNet.

Md. Shaheenur Islam Sumon, Muhammad E. H. Chowdhury, Enamul Hoque Bhuiyan, Md. Sohanur Rahman, Muntakim Mahmud Khan, Israa Al-Hashimi, Adam Mushtak, Sohaib Bassam Zoghoul

Comput. Biol. Medicine, 2025

Deep learning-driven segmentation of ischemic stroke lesions using multi-channel MRI.

Ashiqur Rahman, Muhammad E. H. Chowdhury, Md Sharjis Ibne Wadud, Rusab Sarmun, Adam Mushtak, Sohaib Bassam Zoghoul, Israa Al-Hashimi

Biomed. Signal Process. Control., 2025

Enhanced coronary artery segmentation and stenosis detection: Leveraging novel deep learning techniques.

Abu Jaffor Morshedul Abedin, Rusab Sarmun, Adam Mushtak, Mohamed Sultan Bin Mohamed Ali, Anwarul Hasan, Ponnuthurai Nagaratnam Suganthan, Muhammad E. H. Chowdhury

Biomed. Signal Process. Control., 2025

2024

Automated grading of prenatal hydronephrosis severity from segmented kidney ultrasounds using deep learning.

Sakib Mahmud, Tariq O. Abbas, Muhammad E. H. Chowdhury, Adam Mushtak, Saidul Kabir, Sreekumar Muthiyal, Alaa Koko, Ahmed Balla Abdalla Altyeb, Abdulrahman Alqahtani, Amith Khandakar, Sheikh Mohammed Shariful Islam

Expert Syst. Appl., 2024

Deep learning in computed tomography pulmonary angiography imaging: A dual-pronged approach for pulmonary embolism detection.

Fabiha Bushra, Muhammad E. H. Chowdhury, Rusab Sarmun, Saidul Kabir, Menatalla Said, Sohaib Bassam Zoghoul, Adam Mushtak, Israa Al-Hashimi, Abdulrahman Alqahtani, Anwarul Hasan

Expert Syst. Appl., 2024

Enhancing intima-media complex segmentation with a multi-stage feature fusion-based novel deep learning framework.

Rusab Sarmun, Saidul Kabir, Johayra Prithula, Abdulrahman Alqahtani, Sohaib Bassam Zoghoul, Israa Al-Hashimi, Adam Mushtak, Muhammad E. H. Chowdhury

Eng. Appl. Artif. Intell., 2024

Improving MRI Resolution: A Cycle Consistent Generative Adversarial Network-Based Approach for 3T to 7T Translation.

Zakaria Shams Siam, Rubyat Tasnuva Hasan, Moajjem Hossain Chowdhury, Md. Shaheenur Islam Sumon, Mamun Bin Ibne Reaz, Sawal Hamid Bin Mohd Ali, Adam Mushtak, Israa Al-Hashimi, Sohaib Bassam Zoghoul, Muhammad E. H. Chowdhury

IEEE Access, 2024

2023

Deep learning-based middle cerebral artery blood flow abnormality detection using flow velocity waveform derived from transcranial Doppler ultrasound.

Kanchon Kanti Podder, Muhammad Enamul Hoque Chowdhury, Sumaya Almaadeed, Naima Nasrin Nisha, Sakib Mahmud, Fatema Hamadelneil, Taif Almkhlef, Hind Aljofairi, Adam Mushtak, Amith Khandakar, Susu M. Zughaier

Biomed. Signal Process. Control., August, 2023

PCovNet+: A CNN-VAE anomaly detection framework with LSTM embeddings for smartwatch-based COVID-19 detection.

Farhan Fuad Abir, Muhammad E. H. Chowdhury, Malisha Islam Tapotee, Adam Mushtak, Amith Khandakar, Sakib Mahmud, Anwarul Hasan

Eng. Appl. Artif. Intell., 2023