Ms. Molly O'Brien Profile

Molly O'Brien

at Johns Hopkins University

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Publications (2)

Proceedings Article | 4 April 2022 Presentation + Paper

Evaluating neural network robustness for melanoma classification using mutual information

Molly O'Brien, Julia Bukowski, Greg Hager, Aria Pezeshk, Mathias Unberath

Proceedings Volume 12032, 120320P (2022) https://doi.org/10.1117/12.2612192

KEYWORDS: Melanoma, Neural networks, Skin, Skin cancer, Inspection, Image classification, Detection and tracking algorithms, Data modeling, Cameras

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SPIE Journal Paper | 15 November 2021

Reconstructing the nasal septum from instrument motion during septoplasty surgery

Matthew Holden, Molly O'Brien, Anand Malpani, Hajira Naz, Ya-Wei Tseng, Lisa Ishii, S. Swaroop Vedula, Masaru Ishii, Gregory Hager

JMI, Vol. 8, Issue 06, 065001, (November 2021) https://doi.org/10.1117/12.10.1117/1.JMI.8.6.065001

KEYWORDS: Surgery, Image segmentation, Computed tomography, Nose, Error analysis, Statistical modeling, Motion models, Data modeling, Sensors, Head

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Purpose: Surgery involves modifying anatomy to achieve a goal. Reconstructing anatomy can facilitate surgical care through surgical planning, real-time decision support, or anticipating outcomes. Tool motion is a rich source of data that can be used to quantify anatomy. Our work develops and validates a method for reconstructing the nasal septum from unstructured motion of the Cottle elevator during the elevation phase of septoplasty surgery, without need to explicitly delineate the surface of the septum. Approach: The proposed method uses iterative closest point registration to initially register a template septum to the tool motion. Subsequently, statistical shape modeling with iterative most likely oriented point registration is used to fit the reconstructed septum to Cottle tip position and orientation during flap elevation. Regularization of the shape model and transformation is incorporated. The proposed methods were validated on 10 septoplasty surgeries performed on cadavers by operators of varying experience level. Preoperative CT images of the cadaver septums were segmented as ground truth. Results: We estimated reconstruction error as the difference between the projections of the Cottle tip onto the surface of the reconstructed septum and the ground-truth septum segmented from the CT image. We found translational differences of 2.74 ( 2.06 − 2.81 ) mm and a rotational differences of 8.95 ( 7.11 − 10.55 ) deg between the reconstructed septum and the ground-truth septum [median (interquartile range)], given the optimal regularization parameters. Conclusions: Accurate reconstruction of the nasal septum can be achieved from tool tracking data during septoplasty surgery on cadavers. This enables understanding of the septal anatomy without need for traditional medical imaging. This result may be used to facilitate surgical planning, intraoperative care, or skills assessment.

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