A Nigerian physicist and machine learning expert, Dr. Ikenna Odezuligbo, has developed a revolutionary quantum-inspired AI system that promises to significantly improve early-stage cancer detection. Working with Merck Sharp & Dohme (MSD)—a global pharmaceutical powerhouse—Odezuligbo’s innovation blends advanced physics and artificial intelligence to tackle some of the biggest limitations in modern medical imaging.

This breakthrough comes at a critical time, as cancer remains one of the most lethal diseases globally. According to the World Health Organization (WHO), cancer caused approximately 9.6 million deaths in 2018, accounting for one in six deaths worldwide. The burden continues to grow, placing an enormous strain on individuals, families, and national health systems.

Revolutionising Medical Imaging with Quantum-AI

Dr. Odezuligbo’s invention focuses on enhancing the way artificial intelligence interprets complex medical imaging data—such as MRIs, CT scans, and PET scans—by applying quantum computing principles to improve image clarity and pattern recognition. His approach, referred to as a “quantum-inspired preprocessing method,” tackles one of the key challenges in AI-assisted diagnostics: image inconsistencies caused by rotation, noise, or misalignment.

“These inconsistencies are common in real-world clinical settings,” he explained. “AI models often struggle to correctly identify tumours when images are not perfectly aligned or presented at varying angles. My goal is to change that.”

The Quantum Fourier Transform: A New Frontier

At the core of Odezuligbo’s system is a mathematical innovation known as the quantum Fourier transform (QFT). Borrowed from the field of quantum mechanics, this method re-encodes medical images into the frequency domain, allowing the AI to detect subtle patterns that would otherwise be lost in standard visual interpretation.

By translating spatial images into frequency data, the model becomes invariant to changes in image orientation or size. That means a tumour rotated at a different angle or appearing in an altered position can still be detected with high accuracy. This capability is critical for identifying early-stage or hard-to-detect cancers, particularly in PET-MRI fusion scans, where aligning metabolic and anatomical data is essential.

“Quantum computing and AI aren’t just buzzwords,” Odezuligbo said. “They are rapidly evolving into practical tools with the power to transform clinical decision-making. My system aims to deliver more accurate, reliable, and earlier cancer diagnoses, potentially saving millions of lives.”

Proven Performance and Ongoing Integration

Odezuligbo’s preprocessing system is currently undergoing testing on publicly available medical imaging datasets, and results show significant improvements in both detection accuracy and consistency. His method also reduces false positives and false negatives, addressing a major limitation in conventional AI diagnostics.

Additionally, the system is being integrated into deep learning pipelines and adapted for multi-modal fusion imaging—where two or more imaging methods are combined for comprehensive analysis. One such application is in PET-MRI scans, where precisely matching metabolic and structural information is crucial for accurate tumour identification.

Implications Beyond Cancer Detection

While the primary focus of Odezuligbo’s research is cancer diagnosis, the technology’s potential extends much further. The innovation could prove invaluable in:

• Drug development: Assisting in the screening of how treatments affect tumours over time.

• Biomarker discovery: Identifying molecular signals associated with disease.

• Image-guided therapy: Enhancing surgical accuracy and treatment targeting.

According to the scientist, these applications form part of the growing field of precision medicine, which relies heavily on detailed diagnostics and personalised treatment approaches.

A Vision for the Future of Clinical Imaging

Looking ahead, Dr. Odezuligbo plans to transition from testing on datasets to applying his system on real-world patient data in collaboration with medical institutions. He is also exploring how emerging quantum computers could one day take over the preprocessing workload in real time, making hospital workflows faster and more accurate.

“As healthcare systems across the world race to integrate AI into diagnostics, I believe quantum-enhanced imaging offers a major leap forward,” he said. “By enabling earlier and more reliable detection, this technology can fundamentally reshape how we approach cancer and other life-threatening diseases.”

A Global Innovation Rooted in Nigerian Excellence

Dr. Odezuligbo’s accomplishment highlights the remarkable talent emerging from Nigeria’s scientific community. His work not only places Nigeria on the global map of medical innovation but also underscores the need for greater investment in research, advanced computing, and cross-disciplinary collaboration between academia, medicine, and industry.

If successfully adopted and scaled, this quantum-AI approach could become a cornerstone of diagnostic medicine, not only for Nigeria but for developing and developed countries alike—ushering in a new era where cancer is no longer caught too late.

In a world where early detection can mean the difference between life and death, innovations like Odezuligbo’s are not just scientific achievements—they are beacons of hope.