Purpose: To present a semi-automatic deformable registration algorithm for co-registering T2-weighted (T2w) images of the prostate with whole-mount pathological sections of prostatectomy specimens.
Materials And Methods: Twenty-four patients underwent 1.5 Tesla (T) endorectal MR imaging before radical prostatectomy with whole-mount step-section pathologic analysis of surgical specimens. For each patient, the T2w imaging containing the largest area of tumor was manually matched with the corresponding pathologic slice. The prostate was co-registered using a free-form deformation (FFD) algorithm based on B-splines. Registration quality was assessed through differences between prostate diameters measured in right-left (RL) and anteroposterior (AP) directions on T2w images and pathologic slices and calculation of the Dice similarity coefficient, D, for the whole prostate (WP), the peripheral zone (PZ) and the transition zone (TZ).
Results: The mean differences in diameters measured on pathology and MR imaging in the RL direction and the AP direction were 0.49 cm and -0.63 cm, respectively, before registration and 0.10 cm and -0.11 cm, respectively, after registration. The mean D values for the WP, PZ and TZ, were 0.76, 0.65, and 0.77, respectively, before registration and increased to 0.91, 0.76, and 0.85, respectively, after registration. The improvements in D were significant for all three tissues (P < 0.001 for all).
Conclusion: The proposed semi-automatic method enabled successful co-registration of anatomical prostate MR images to pathologic slices.
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http://dx.doi.org/10.1002/jmri.22347 | DOI Listing |
Med Phys
January 2025
Department of Radiation Oncology, Duke University, Durham, North Carolina, USA.
Purpose: Evaluating deformable image registration (DIR) algorithms is vital for enhancing algorithm performance and gaining clinical acceptance. However, there is a notable lack of dependable DIR benchmark datasets for assessing DIR performance except for lung images. To address this gap, we aim to introduce our comprehensive liver computed tomography (CT) DIR landmark dataset library.
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Institute of Cognition, Brain and Health, Henan University, Kaifeng 475004, China.
Reward processing deficit is a core feature of schizophrenia, however, it remains unclear whether reward processing is impaired in individuals with high schizotypy. In this study, 27 high schizotypal trait and 25 control group children were screened by the Chinese version of the Schizotypal Personality Questionnaire for Children (SPQC). We recorded their brain activity (event-related potentials, ERPs) while they completed a simple gambling task.
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Future Robotics Organization, Waseda University, Tokyo, 1620044, Japan.
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Department of Circulation and Medical Imaging, NTNU-Norwegian University of Science and Technology, Box 8905, 7491 Trondheim, Norway.
Comput Biol Med
December 2024
Department of Computer Engineering, Faculty of Intelligent Systems Engineering and Data Science, Persian Gulf University, Bushehr, 7516913817, Iran.
Breast cancer ranks as the second most prevalent cancer in women, recognized as one of the most dangerous types of cancer, and is on the rise globally. Regular screenings are essential for early-stage treatment. Digital mammography (DM) is the most recognized and widely used technique for breast cancer screening.
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