Project Week 25/NeedleSegmentation

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Key Investigators

• Paolo Zaffino (Magna Graecia University, Italy)
• Salvatore Scaramuzzino (Magna Graecia University/ASL Vercelli, Italy)
• Maria Francesca Spadea (Magna Graecia University, Italy)
• Guillaume Pernelle (remote) (Imperial College, London, UK)
• Alireza Mehrtash (remote) (Brigham and Women's Hospital, Harvard Medical School, USA)
• Tina Kapur (Brigham and Women's Hospital, Harvard Medical School, USA)

Project Description

NeedleFinder offers tools to segment needles from MRI/CT. It has mostly been tested on MRI from GYN brachytherapy cases. Anyway, this tool requires manual interaction. Now we want to develop a completely automatic strategy to segment the needles. For this purpose, we tested a CNN approach that provides good results, even if a post processing step must be implemented in order to remove some noise and to refine the obtained segmentations.

Objective	Approach and Plan	Progress and Next Steps
Refine/clear the segmentations coming from the CNN algorithm. Figure out how to transfer MRIs to some server hosting the CNN code and how to get back the results.	Clustering and morphological filter for data cleaning. Talk with someone of core team to figure out how to remotely process the data.	TDB

Illustrations

Background and References

1. NeedleFinder website
2. Model-based Catheter Segmentation in MRI-images