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International Conference on Medical Imaging and Machine Learning

ICMIML

5th Mar – 6th Mar 2027 British Columbia, Canada

Official Invitation Letter Available

An official invitation letter will be provided upon successful registration for your participation in the conference.

Benefits of Registering as Listener

Access to All Conference Sessions

Plenary, keynote and parallel sessions

Networking Opportunities

Connect with global educators & researchers

Certificate of Participation

Digital certificate of participation

Invitation Letter Support

Official invitation letter after successful registration

Conference Kit / Digital Materials

E-proceedings & resource materials

Access to Keynote Sessions

Learn from leading experts & scholars

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Terms & Condition

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Conference Session Tracks

UN SDG Wheel

Aligned with UN Sustainable Development Goals

The conference's session tracks effectively support the following SDGs.

SDG 3 SDG 9 SDG 10
01 Advancements in Image Segmentation Techniques +
This track focuses on the latest methodologies in image segmentation within medical imaging. Researchers are invited to present novel algorithms and frameworks that enhance the accuracy and efficiency of segmentation processes.
SDG 3 SDG 9
02 Machine Learning Approaches for Image Classification +
This session explores innovative machine learning techniques for classifying medical images. Contributions should highlight advancements in supervised and unsupervised learning paradigms tailored for diagnostic purposes.
SDG 3 SDG 9
03 Feature Extraction and Selection in Medical Imaging +
This track emphasizes the importance of feature extraction and selection in enhancing machine learning models for medical imaging. Participants are encouraged to discuss new methods that improve the interpretability and performance of predictive models.
SDG 3 SDG 9
04 Pattern Recognition in Radiological Data +
This session delves into the application of pattern recognition techniques in analyzing radiological images. Papers should address challenges and solutions in detecting anomalies and patterns that aid in diagnosis.
SDG 3 SDG 9
05 Predictive Modeling in Healthcare Analytics +
This track focuses on the development of predictive models that leverage machine learning for healthcare analytics. Submissions should demonstrate the impact of these models on patient outcomes and clinical decision-making.
SDG 3 SDG 10
06 Deep Learning Innovations in Imaging +
This session highlights cutting-edge deep learning methodologies applied to medical imaging. Researchers are invited to present their findings on neural networks and their effectiveness in various imaging tasks.
SDG 3 SDG 9
07 Anomaly Detection in Medical Imaging +
This track addresses the critical area of anomaly detection in medical images using machine learning techniques. Contributions should focus on novel approaches that enhance the identification of rare or unusual patterns.
SDG 3 SDG 10
08 Computer-Aided Diagnosis Systems +
This session explores the integration of machine learning in computer-aided diagnosis systems. Papers should discuss the design, implementation, and evaluation of systems that assist radiologists in clinical settings.
SDG 3 SDG 10
09 Neural Networks for Imaging Applications +
This track focuses on the application of various neural network architectures in medical imaging tasks. Researchers are encouraged to share insights on model performance and real-world applications.
SDG 3 SDG 10
10 Object Detection Techniques in Medical Imaging +
This session investigates the latest advancements in object detection methodologies for medical imaging. Contributions should emphasize the challenges and solutions in accurately identifying anatomical structures and pathologies.
SDG 3 SDG 10
11 Visual Analytics in Medical Imaging +
This track emphasizes the role of visual analytics in interpreting complex medical imaging data. Participants are invited to present innovative tools and techniques that enhance data visualization and decision support.
SDG 3 SDG 9