{"@context":"http://iiif.io/api/presentation/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/manifest.json","@type":"sc:Manifest","label":"Improvements in Lesion Detection in X-Ray Breast Tomosynthesis and in Emission Tomography","metadata":[{"label":"dc.description.sponsorship","value":"This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree."},{"label":"dc.format","value":"Monograph"},{"label":"dc.format.medium","value":"Electronic Resource"},{"label":"dc.identifier.uri","value":"http://hdl.handle.net/11401/77478"},{"label":"dc.language.iso","value":"en_US"},{"label":"dc.publisher","value":"The Graduate School, Stony Brook University: Stony Brook, NY."},{"label":"dcterms.abstract","value":"Cancerous lesions can be viewed using several medical imaging modalities. I address breast cancer as seen in contrast-enhanced dual-energy digital breast tomosynthesis (CE-DE-DBT) and liver imaging of liver neuroendocrine metastases as seen by SPECT (Single Photon Emission Computed Tomography). The overall goal is to enhance the ability to detect such lesions by improvements in image acquisition and data processing methods. In CE-DE-DBT the presence of scattered photons can yield image artifacts that mask the breast lesion. I present a scatter correction method based on interpolating scatter tails at the image periphery. I validate the method using a pinhole array technique and beam blocker method. CE-DE-DBT is also easily corrupted by patient motion. Acquiring the image using interleaved acquisition can aid in minimizing patient motion artifacts, but introduces new artifacts when combined with standard CE-DE-DBT processing methods. I introduce a modification of the post-acquisition processing - a " reconstruct-then-subtract" method that minimizes these artifacts. Then choice of reconstruction algorithm in the reconstruct-then-subtract method can also influence image quality. I demonstrate that the use of a statistical reconstruction technique, ordered subsets transmission tomography, can aid in visualizing small lesions. For SPECT, the collimator is the crucial element controlling the noise/resolution tradeoff in the image. The best collimator will yield the best performance on a task of detecting and localizing the lesion. I use the tools of statistical decision theory on a performance metric based on the area under the localization receiver operating characteristic curve to optimize the collimator design, taking into account the important physical effects of collimator septal penetration and scatter by the high energy photons of the In-111 radionuclide. The optimal parallel-collimator is characterized by geometrical parameters (bore length, bore width, septal thickness) that allow a controlled number of photons from septal scatter and penetration into the image."},{"label":"dcterms.available","value":"2017-09-20T16:52:46Z"},{"label":"dcterms.contributor","value":"Gindi, Gene"},{"label":"dcterms.creator","value":"Lu, Yihuan"},{"label":"dcterms.dateAccepted","value":"2017-09-20T16:52:46Z"},{"label":"dcterms.dateSubmitted","value":"2017-09-20T16:52:46Z"},{"label":"dcterms.description","value":"Department of Electrical Engineering."},{"label":"dcterms.extent","value":"187 pg."},{"label":"dcterms.format","value":"Monograph"},{"label":"dcterms.identifier","value":"http://hdl.handle.net/11401/77478"},{"label":"dcterms.issued","value":"2015-12-01"},{"label":"dcterms.language","value":"en_US"},{"label":"dcterms.provenance","value":"Made available in DSpace on 2017-09-20T16:52:46Z (GMT). No. of bitstreams: 1\nLu_grad.sunysb_0771E_12283.pdf: 4476057 bytes, checksum: 6e03a98cfbc9885b8ed665addb15881e (MD5)\n  Previous issue date:    1"},{"label":"dcterms.publisher","value":"The Graduate School, Stony Brook University: Stony Brook, NY."},{"label":"dcterms.subject","value":"collimator optimization, Contrast Enhanced Dual Energy Digital Breast Tomosynthesis, ideal observer, reconstruction, scatter correction, Single Photon Emission Computed Tomography"},{"label":"dcterms.title","value":"Improvements in Lesion Detection in X-Ray Breast Tomosynthesis and in Emission Tomography"},{"label":"dcterms.type","value":"Dissertation"},{"label":"dc.type","value":"Dissertation"}],"description":"This manifest was generated dynamically","viewingDirection":"left-to-right","sequences":[{"@type":"sc:Sequence","canvases":[{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json","@type":"sc:Canvas","label":"Page 1","height":1650,"width":1275,"images":[{"@type":"oa:Annotation","motivation":"sc:painting","resource":{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/10%2F50%2F95%2F10509583749786551357947162396242124727/full/full/0/default.jpg","@type":"dctypes:Image","format":"image/jpeg","height":1650,"width":1275,"service":{"@context":"http://iiif.io/api/image/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/10%2F50%2F95%2F10509583749786551357947162396242124727","profile":"http://iiif.io/api/image/2/level2.json"}},"on":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json"}]}]}]}