Charles Cockrell

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Multidetector computed tomography (MDCT) has emerged as the imaging modality of choice for evaluating the abdomen and pelvis in trauma patients. MDCT readily detects injury of the solid organs as well as direct and indirect features of bowel and/or mesenteric injury—an important advance given that unrecognized bowel and mesenteric injuries may result in(More)
In this paper we present an automated system based mainly on the computed tomography (CT) images consisting of two main components: the midline shift estimation and intracranial pressure (ICP) pre-screening system. To estimate the midline shift, first an estimation of the ideal midline is performed based on the symmetry of the skull and anatomical features(More)
Biochemical recurrence after treatment for prostate cancer (PCa) is a significant issue. Early diagnosis of local recurrence is important for making prompt treatment decisions and is strongly associated with patient prognosis. Without salvage therapy, the average time from development of local recurrence to distant metastasis is approximately 3 years.(More)
Spleen segmentation is especially challenging as the majority of solid organs in the abdomen region have similar gray level range. Physician analysis of computed tomography (CT) images to assess abdominal trauma could be very time consuming and hence, automating this process can reduce time to treatment. The proposed method presented in this paper is a(More)
One in six males will develop prostate cancer during their lifetime. Prostate cancer is the second leading cause of cancer death in American males, behind only lung cancer. Unfortunately, even though this disease is so common, clinical screening methods such as prostate-specific antigen test and transrectal ultrasound-guided prostate biopsy lack sensitivity(More)
Brain ideal midline estimation is vital in medical image processing, especially in analyzing the severity of a brain injury in clinical environments. We propose an automated computer-aided ideal midline estimation system with a two-step process. First, a CT Slice Selection Algorithm (SSA) can automatically select an appropriate subset of slices from a large(More)
BACKGROUND The analysis of pelvic CT scans is a crucial step for detecting and assessing the severity of Traumatic Pelvic Injuries. Automating the processing of pelvic CT scans could impact decision accuracy, decrease the time for decision making, and reduce health care cost. This paper discusses a method to automate the segmentation of bone from pelvic CT(More)
Automated hemorrhage detection and segmentation in traumatic pelvic injuries is vital for fast and accurate treatment decision making. Hemorrhage is the main cause of deaths in patients within first 24 hours after the injury. It is very time consuming for physicians to analyze all Computed Tomography (CT) images manually. As time is crucial in emergence(More)
A renal transplant recipient developed acute renal transplant vein thrombosis following surgery for a total hip replacement. As an alternative to standard surgical therapy, the patient was treated with selective intravenous low-dose infusion of streptokinase at doses of 5,000–20,000 units/h. The infusion was continued for 120 h with constant monitoring of(More)
Pelvic bone segmentation is a vital step in analyzing pelvic CT images, which assists physicians with diagnostic decision making in cases of traumatic pelvic injuries. Due to the limited resolution of the original CT images and the complexity of pelvic structures and their possible fractures, automatic pelvic bone segmentation in multiple CT slices is very(More)