{"id":45947,"date":"2023-11-20T05:44:15","date_gmt":"2023-11-20T11:44:15","guid":{"rendered":"https:\/\/stage.cancerimagingarchive.net\/analysis-result\/prostatex-seg-hires\/"},"modified":"2025-03-20T13:38:10","modified_gmt":"2025-03-20T18:38:10","slug":"prostatex-seg-hires","status":"publish","type":"tcia_analysis_result","link":"https:\/\/stage.cancerimagingarchive.net\/analysis-result\/prostatex-seg-hires\/","title":{"rendered":"PROSTATEX-SEG-HIRES"},"featured_media":8929,"template":"","class_list":["post-45947","tcia_analysis_result","type-tcia_analysis_result","status-publish","has-post-thumbnail"],"cancer_types":["Prostate"],"citations":[45939,45941,9225],"result_doi":"10.7937\/tcia.2019.deg7zg1u","result_download_info":"","result_downloads":[45943],"version_change_log_archived":"Version 1 (Current): 2020\/09\/18\r\n Data TypeDownload all or Query\/FilterSegmentations (DICOM,\u00a00.119 GB)\u00a0 \u00a0\u00a0Corresponding Original MR Images from PROSTATEx (DICOM, 371.21 MB)\u00a0 \u00a0\u00a0","versions":false,"additional_resources":"","cancer_locations":["Prostate"],"publications_related":"","result_page_accessibility":"Public","detailed_description":"","publications_using":"TCIA maintains a list of publications<\/a> that leverage TCIA data. If you have a manuscript you'd like to add please contact TCIA's Helpdesk<\/a>.","result_title":"High Resolution Prostate Segmentations for the ProstateX-Challenge","species":["Human"],"version_number":"1","date_updated":"2020-09-18","related_collections":[43659],"result_short_title":"PROSTATEx-Seg-HiRes","subjects":"66","related_analysis_results":false,"result_browse_title":"High Resolution Prostate Segmentations for the ProstateX-Challenge (PROSTATEx-Seg-HiRes)","supporting_data":["Organ segmentations"],"version_change_log":"","collections":"","result_summary":"We created 66 high resolution segmentations for randomly chosen T2-weighted volumes of the\u00a0SPIE-AAPM-NCI PROSTATEx Challenges (PROSTATEx)<\/a>. The high\u00a0resolution segmentations were obtained\u00a0by\u00a0considering the three scan directions: for each scan direction (axial, sagittal, coronal),\u00a0the gland was manually delineated by a medical student, followed\u00a0by a review and corrections of an expert urologist.\u00a0These three anisotropic segmentations were fused to one isotropic segmentation by means of shape-based interpolation\u00a0in the following manner: (1) The signed distance transformation of the three segmentations is computed.\u00a0(2) The anisotropic distance volumes are transformed into an isotropic high-resolution representation with linear interpolation. (3) By averaging the distances, smoothing and thresholding them at zero, we obtained the fused segmentation. The resulting segmentations were manually verified and corrected further by the expert urologist if necessary.\u00a0Serving as ground truth for training CNNs, these segmentations have the potential to improve the segmentation accuracy of automated algorithms. By considering not only the axial scans but also sagittal and coronal scan directions, we aimed to have higher fidelity of the segmentations especially at the apex and base regions of the prostate.\r\n\r\nThe segmentations to standard DICOM representation were created with dcmqi<\/a>\u00a0<\/em>","collection_downloads":[45945],"result_featured_image":{"ID":"8929","post_author":"29","post_date":"2023-09-14 01:02:01","post_date_gmt":"2023-09-14 06:02:01","post_content":"","post_title":"High-Resolution","post_excerpt":"","post_status":"inherit","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"high-resolution","to_ping":"","pinged":"","post_modified":"2023-11-20 05:44:15","post_modified_gmt":"2023-11-20 11:44:15","post_content_filtered":"","post_parent":"45947","guid":"https:\/\/stage.cancerimagingarchive.net\/wp-content\/uploads\/High-Resolution.jpg","menu_order":"0","post_type":"attachment","post_mime_type":"image\/jpeg","comment_count":"0","pod_item_id":"8929"},"result_acknowledgements":"