Hannan Abdillahi - Academia.edu (original) (raw)
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Papers by Hannan Abdillahi
Investigative Ophthalmology & Visual Science, 2012
The application of a novel data and physics driven modeling technique integrating many data sourc... more The application of a novel data and physics driven modeling technique integrating many data sources such as historical production and injection data, wellbore andcompletions data for a mature waterflood in the Cuyo basin in Argentina is presented. This innovative technology combines the benefits of speed of machine learning with the predictivity capabilities of traditional simulation. The initial objective was to identify opportunities for optimization of ongoingsecondary recovery projects to increase production and reduce costs in the subject field. During the execution of the project the need to evaluatereactivation of inactive injectors was identified and the software was modified to include this feature. The technology integrates machine learning techniques with partial differential equations of fluid flow such as thoseapplied in conventional reservoirs simulation models. Because the presented approach honors reservoir physics, it provides long term predictivecapacity and always...
Investigative Ophthalmology & Visual Science, 2014
Investigative Ophthalmology & Visual Science, 2013
Stem Cell & Translational Investigation, 2015
The bone marrow (BM) is home to different stem/progenitor populations, including tissue-committed... more The bone marrow (BM) is home to different stem/progenitor populations, including tissue-committed stem cells. In this context, we have cocultured BM-derived stem cells (BMSC) in order to investigate their differentiation capacity towards the retinal pigment epithelial (RPE) lineage in vitro. Furthermore, pre-differentiated BMSC were transplanted into the pharmacologically damaged subretinal space to determine their rescue ability in vivo. BM was harvested from the tibias and femurs of adult GFP + C57BL/6 mice. Differentiated hematopoietic cells were removed by lineage depletion, and CD45-BMSCs were separated by magnetic activated cell sorting (MACS). To induce differentiation, the cells were then cocultured with murine RPE for 10 days, and retinal markers were assessed using immunohistochemistry (IHC). To induce retinal degeneration, mice were treated with sodium iodate (NaIO 3). Seven days later, approx. 60,000 pre-differentiated GFP + BMSC, sorted by FACS, were transplanted subretinally. Optical coherence tomography (OCT) was used to follow the transplants and to quantify the retinal thickness over time. Visual acuity was measured concurrently using the optokinetic reflex (OKR). Finally, IHC was performed to investigate the expression of retina-specific markers in the transplants. CD45-BMSC adopted an RPE-like elongated morphology and showed expression of the RPE markers RPE65 and bestrophin after coculture. After transplantation of CD45-BMSC, visual acuity increased in individual animals compared to the contralateral control eye, but did not reach baseline levels. Additionally, no significant increase in retinal thickness in the transplanted eye was found. However, the cells were detectable in the subretinal space for up to 28 days and expressed the RPE markers RPE65 and bestrophin. In summary, the BMSC differentiated into RPE-like cells but were not able to restore visual function or rescue retinal morphology after subretinal transplantation.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012, 2012
With improvements in acquisition speed and quality, the amount of medical image data to be screen... more With improvements in acquisition speed and quality, the amount of medical image data to be screened by clinicians is starting to become challenging in the daily clinical practice. To quickly visualize and find abnormalities in medical images, we propose a new method combining segmentation algorithms with statistical shape models. A statistical shape model built from a healthy population will have a close fit in healthy regions. The model will however not fit to morphological abnormalities often present in the areas of pathologies. Using the residual fitting error of the statistical shape model, pathologies can be visualized very quickly. This idea is applied to finding drusen in the retinal pigment epithelium (RPE) of optical coherence tomography (OCT) volumes. A segmentation technique able to accurately segment drusen in patients with age-related macular degeneration (AMD) is applied. The segmentation is then analyzed with a statistical shape model to visualize potentially pathological areas. An extensive evaluation is performed to validate the segmentation algorithm, as well as the quality and sensitivity of the hinting system. Most of the drusen with a height of 85.5µm were detected, and all drusen at least 93.6µm high were detected.
IEEE Transactions on Medical Imaging, 2013
Optical Coherence Tomography is a well established image modality in ophthalmology and used daily... more Optical Coherence Tomography is a well established image modality in ophthalmology and used daily in the clinic. Automatic evaluation of such datasets requires an accurate segmentation of the retinal cell layers. However, due to the naturally low signal to noise ratio and the resulting bad image quality, this task remains challenging. We propose an automatic graphbased multi-surface segmentation algorithm that internally uses soft constraints to add prior information from a learned model. This improves the accuracy of the segmentation and increase the robustness to noise. Furthermore, we show that the graph size can be greatly reduced by applying a smart segmentation scheme. This allows the segmentation to be computed in seconds instead of minutes, without deteriorating the segmentation accuracy, making it ideal for a clinical setup. An extensive evaluation on 20 OCT datasets of healthy eyes was performed and showed a mean unsigned segmentation error of 3.05 ± 0.54µm over all datasets when compared to the average observer, which is lower than the inter-observer variability. Similar performance was measured for the task of drusen segmentation, demonstrating the usefulness of using soft constraints as a tool to deal with pathologies.
Purpose: Geographic atrophy (GA) is the end-stage manifestation of atrophic age-related macular d... more Purpose: Geographic atrophy (GA) is the end-stage manifestation of atrophic age-related macular degeneration (AMD). The disease progresses slowly over time, eventually causing loss of central vision. Its cause and pathomechanism are not fully known. Previous studies have suggested that vitreoretinal traction (VRT) may contribute to the progression of neovascular AMD. The aim of this study was to examine whether an association between changes at the vitreoretinal interface (VRI), in particular traction (VRT), and the characteristics and progression of GA in eyes with dry AMD can be established. Design: Clinic-based prospective cohort study. Participants: A total of 97 patients (age range, 61e90 years; mean, 78.4 years) with GA secondary to dry AMD were enrolled. Patients exhibiting neovascular signs on fluorescein angiography in either eye were excluded. Methods: The VRI changes were examined using spectral-domain optical coherence tomography (SD-OCT). Characteristics of GA were examined using fundus autofluorescence (FAF) imaging. All imaging was performed using a Spectralis SLOþOCT device (Heidelberg Engineering, Heidelberg, Germany); GA area was measured using the Region Finder (Heidelberg Engineering) software native to the Spectralis platform. Main Outcome Measures: Area and increase in area of GA. Results: A total of 97 eyes were examined. Vitreoretinal traction was found in 39 eyes (40%). The GA area at baseline was 6.65AE5.64 mm 2 in eyes with VRT and 5.73AE4.72 mm 2 in eyes with no VRT. The annual rate of progression of GA area progression was 2.99AE0.66 mm 2 in eyes with VRT and 1.45AE0.67mm 2 in eyes without VRT. Differences between groups in both parameters were statistically significant (n ¼ 97 total number of eyes; P<0.001). Multiple regression analysis confirmed this finding (B ¼ 0.714, P<0.001; F 3,93 ¼ 72.542, P<0.001; adjusted R 2 ¼ 0.691) Conclusions: Our results indicate an association between VRT and an increased rate of progression of GA area in dry AMD. Monitoring VRT may contribute to an improved estimate of the prospective time of visual loss and to a better timing of emerging therapies in dry AMD.
Investigative Ophthalmology & Visual Science, 2012
The application of a novel data and physics driven modeling technique integrating many data sourc... more The application of a novel data and physics driven modeling technique integrating many data sources such as historical production and injection data, wellbore andcompletions data for a mature waterflood in the Cuyo basin in Argentina is presented. This innovative technology combines the benefits of speed of machine learning with the predictivity capabilities of traditional simulation. The initial objective was to identify opportunities for optimization of ongoingsecondary recovery projects to increase production and reduce costs in the subject field. During the execution of the project the need to evaluatereactivation of inactive injectors was identified and the software was modified to include this feature. The technology integrates machine learning techniques with partial differential equations of fluid flow such as thoseapplied in conventional reservoirs simulation models. Because the presented approach honors reservoir physics, it provides long term predictivecapacity and always...
Investigative Ophthalmology & Visual Science, 2014
Investigative Ophthalmology & Visual Science, 2013
Stem Cell & Translational Investigation, 2015
The bone marrow (BM) is home to different stem/progenitor populations, including tissue-committed... more The bone marrow (BM) is home to different stem/progenitor populations, including tissue-committed stem cells. In this context, we have cocultured BM-derived stem cells (BMSC) in order to investigate their differentiation capacity towards the retinal pigment epithelial (RPE) lineage in vitro. Furthermore, pre-differentiated BMSC were transplanted into the pharmacologically damaged subretinal space to determine their rescue ability in vivo. BM was harvested from the tibias and femurs of adult GFP + C57BL/6 mice. Differentiated hematopoietic cells were removed by lineage depletion, and CD45-BMSCs were separated by magnetic activated cell sorting (MACS). To induce differentiation, the cells were then cocultured with murine RPE for 10 days, and retinal markers were assessed using immunohistochemistry (IHC). To induce retinal degeneration, mice were treated with sodium iodate (NaIO 3). Seven days later, approx. 60,000 pre-differentiated GFP + BMSC, sorted by FACS, were transplanted subretinally. Optical coherence tomography (OCT) was used to follow the transplants and to quantify the retinal thickness over time. Visual acuity was measured concurrently using the optokinetic reflex (OKR). Finally, IHC was performed to investigate the expression of retina-specific markers in the transplants. CD45-BMSC adopted an RPE-like elongated morphology and showed expression of the RPE markers RPE65 and bestrophin after coculture. After transplantation of CD45-BMSC, visual acuity increased in individual animals compared to the contralateral control eye, but did not reach baseline levels. Additionally, no significant increase in retinal thickness in the transplanted eye was found. However, the cells were detectable in the subretinal space for up to 28 days and expressed the RPE markers RPE65 and bestrophin. In summary, the BMSC differentiated into RPE-like cells but were not able to restore visual function or rescue retinal morphology after subretinal transplantation.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012, 2012
With improvements in acquisition speed and quality, the amount of medical image data to be screen... more With improvements in acquisition speed and quality, the amount of medical image data to be screened by clinicians is starting to become challenging in the daily clinical practice. To quickly visualize and find abnormalities in medical images, we propose a new method combining segmentation algorithms with statistical shape models. A statistical shape model built from a healthy population will have a close fit in healthy regions. The model will however not fit to morphological abnormalities often present in the areas of pathologies. Using the residual fitting error of the statistical shape model, pathologies can be visualized very quickly. This idea is applied to finding drusen in the retinal pigment epithelium (RPE) of optical coherence tomography (OCT) volumes. A segmentation technique able to accurately segment drusen in patients with age-related macular degeneration (AMD) is applied. The segmentation is then analyzed with a statistical shape model to visualize potentially pathological areas. An extensive evaluation is performed to validate the segmentation algorithm, as well as the quality and sensitivity of the hinting system. Most of the drusen with a height of 85.5µm were detected, and all drusen at least 93.6µm high were detected.
IEEE Transactions on Medical Imaging, 2013
Optical Coherence Tomography is a well established image modality in ophthalmology and used daily... more Optical Coherence Tomography is a well established image modality in ophthalmology and used daily in the clinic. Automatic evaluation of such datasets requires an accurate segmentation of the retinal cell layers. However, due to the naturally low signal to noise ratio and the resulting bad image quality, this task remains challenging. We propose an automatic graphbased multi-surface segmentation algorithm that internally uses soft constraints to add prior information from a learned model. This improves the accuracy of the segmentation and increase the robustness to noise. Furthermore, we show that the graph size can be greatly reduced by applying a smart segmentation scheme. This allows the segmentation to be computed in seconds instead of minutes, without deteriorating the segmentation accuracy, making it ideal for a clinical setup. An extensive evaluation on 20 OCT datasets of healthy eyes was performed and showed a mean unsigned segmentation error of 3.05 ± 0.54µm over all datasets when compared to the average observer, which is lower than the inter-observer variability. Similar performance was measured for the task of drusen segmentation, demonstrating the usefulness of using soft constraints as a tool to deal with pathologies.
Purpose: Geographic atrophy (GA) is the end-stage manifestation of atrophic age-related macular d... more Purpose: Geographic atrophy (GA) is the end-stage manifestation of atrophic age-related macular degeneration (AMD). The disease progresses slowly over time, eventually causing loss of central vision. Its cause and pathomechanism are not fully known. Previous studies have suggested that vitreoretinal traction (VRT) may contribute to the progression of neovascular AMD. The aim of this study was to examine whether an association between changes at the vitreoretinal interface (VRI), in particular traction (VRT), and the characteristics and progression of GA in eyes with dry AMD can be established. Design: Clinic-based prospective cohort study. Participants: A total of 97 patients (age range, 61e90 years; mean, 78.4 years) with GA secondary to dry AMD were enrolled. Patients exhibiting neovascular signs on fluorescein angiography in either eye were excluded. Methods: The VRI changes were examined using spectral-domain optical coherence tomography (SD-OCT). Characteristics of GA were examined using fundus autofluorescence (FAF) imaging. All imaging was performed using a Spectralis SLOþOCT device (Heidelberg Engineering, Heidelberg, Germany); GA area was measured using the Region Finder (Heidelberg Engineering) software native to the Spectralis platform. Main Outcome Measures: Area and increase in area of GA. Results: A total of 97 eyes were examined. Vitreoretinal traction was found in 39 eyes (40%). The GA area at baseline was 6.65AE5.64 mm 2 in eyes with VRT and 5.73AE4.72 mm 2 in eyes with no VRT. The annual rate of progression of GA area progression was 2.99AE0.66 mm 2 in eyes with VRT and 1.45AE0.67mm 2 in eyes without VRT. Differences between groups in both parameters were statistically significant (n ¼ 97 total number of eyes; P<0.001). Multiple regression analysis confirmed this finding (B ¼ 0.714, P<0.001; F 3,93 ¼ 72.542, P<0.001; adjusted R 2 ¼ 0.691) Conclusions: Our results indicate an association between VRT and an increased rate of progression of GA area in dry AMD. Monitoring VRT may contribute to an improved estimate of the prospective time of visual loss and to a better timing of emerging therapies in dry AMD.