DSpace Repository :: Browsing by Author "Milano, Federico E."

Browsing by Author "Milano, Federico E."

Now showing 1 - 7 of 7

Clasificación de lesiones cutáneas utilizando métodos de procesamiento de imágenes y aprendizaje profundo
(2019-10-10) Choi, David Fabián; Migliano, Luciana; Milano, Federico E.; Mosquera, Tomás
El objetivo general de este trabajo es "desarrollar métodos de detección precoz de melanoma mediante el uso de un sistema automatizado."
Exactitud dimensional en cirugía asistida por computadora
(2016-02) Milano, Federico E.; Risk, Marcelo
"El estudio y aplicación de la cirugía asistida por computadora ha crecido notablemente en los últimos diez años, de la mano del veloz incremento del poder de cómputo de procesadores a un costo accesible. A su vez, este mismo fenómeno impulsó a que la mayoría de los dispositivos de adquisición de imágenes médicas comenzaran a trabajar totalmente en forma digital, facilitando la aparición de subcampos relacionados a la cirugía asistida por computadora, como la planificación preoperatoria en un escenario tridimensional interactivo y la digitalización de piezas óseas para transplantes en un banco de huesos virtual. Esta tesis trata sobre dos problemas que surgen al utilizar estas nuevas tecnologías en la ortopedia oncológica".
In vitro comparative study between conventional and computer-assisted surgery methods for planning and resection of bone sarcomas
(2017-08) Ritacco, Lucas E.; Aponte-Tinao, Luis A.; Múscolo, D. Luis; Ayerza, Miguel A.; Albergo, José I.; Farfalli, Germán L.; Risk, Marcelo; González Bernaldo de Quirós, Fernán; Milano, Federico E.
"This poster aims to achieve an “in vitro” comparative study between three methods: 2D digital images planning and execution without navigation (freehand with ruler and caliper), 3D planning and execution without navigation (freehand with ruler and caliper) and 3D planning and execution guided with navigation. 3D planning and navigated procedures potentially improve sarcoma resection."
Is needle biopsy clinically useful in preoperative grading of central chondrosarcoma of the pelvis and long bones?
(2017) Roitman, Pablo D.; Farfalli, Germán L.; Ayerza, Miguel A.; Múscolo, D. Luis; Milano, Federico E.; Aponte-Tinao, Luis A.
"Central chondrosarcoma of bone is graded on a scale of 1 to 3 according to histological criteria. Clinically, these tumors can be divided into low-grade (Grade 1) and high-grade (Grade 2, Grade 3, and dedifferentiated) chondrosarcomas. Although en bloc resection has been the most widely used treatment, it has become generally accepted that in selected patients with low-grade chondrosarcomas of long bones, curettage is safe and effective. This approach requires an accurate preoperative estimation of grade to avoid under- or overtreatment, but prior reports have indicated that both imaging and biopsy do not always give an accurate prediction of grade."
Obtaining accurate and calibrated coil models for transcranial magnetic stimulation using magnetic field measurements
(2020) Mancino, Axel; Milano, Federico E.; Martín-Bertuzzi, Fiorella; Yampolsky, C. G.; Ritacco, Lucas E.; Risk, Marcelo
"Currently, simulations of the induced currents in the brain produced by transcranial magnetic stimulation (TMS) are used to elucidate the regions reached by stimuli. However, models commonly found in the literature are too general and neglect imperfections in the windings. Aiming to predict the stimulation sites in patients requires precise modeling of the electric field (E-field), and a proper calibration to adequate to the empirical data of the particular coil employed. Furthermore, most fabricators do not provide precise information about the coil geometries, and even using X-ray images may lead to subjective interpretations. We measured the three components of the vector magnetic field induced by a TMS figure-8 coil with spatial resolutions of up to 1 mm. Starting from a computerized tomography-based coil model, we applied a multivariate optimization algorithm to automatically modify the original model and obtain one that optimally fits the measurements. Differences between models were assessed in a human brain mesh using the finite-elements method showing up to 6% variations in the E-field magnitude. Our calibrated model could increase the precision of the estimated E-field induced in the brain during TMS, enhance the accuracy of delivered stimulation during functional brain mapping, and improve dosimetry for repetitive TMS."
Software para facilitar la localización de estructuras subcorticales que son blanco de electroestimulación
(2019-08-09) Oxenford, Simón; Milano, Federico E.
"La localización de los ganglios basales en imágenes de Resonancia Magnética Nuclear de 1.5T y 3T es un problema difícil, inclusive para neurocirujanos especializados. Una correcta localización de estos núcleos es importante para lograr buenos resultados en procedimientos quirúrgicos de implantación de electrodos profundos para estimulación cerebral profunda (Deep Brain Stimulation, DBS). En este trabajo aplicamos métodos de registración deformable de atlas cerebrales de reciente publicación para obtener una localización adecuada de estas estructuras. A su vez, reconstruimos la localización de los electrodos a partir de imágenes de Tomografía Computada con la finalidad de ver la disposición de los contactos con respecto a los núcleos. De esta forma se plantea asistir al cirujano en la conguración de la estimulación de cada paciente. Evaluamos la localización de los núcleos por medio de la comparación con imágenes pre y post operatorias en base a casos reales que cuentan con dichos estudios. Por último, extendimos un software de análisis y visualización de imágenes médicas al que integramos los algoritmos ya mencionados para que los resultados puedan ser validados por médicos especialistas."
What is the expected learning curve in computer-assisted navigation for bone tumor resection?
(2017) Farfalli, Germán L.; Albergo, José I.; Ritacco, Lucas E.; Ayerza, Miguel A.; Milano, Federico E.; Aponte-Tinao, Luis A.
"Background Computer navigation during surgery can help oncologic surgeons perform more accurate resections. However, some navigation studies suggest that this tool may result in unique intraoperative problems and increased surgical time. The degree to which these problems might diminish with experience–the learning curve–has not, to our knowledge, been evaluated for navigation-assisted tumor resections. Questions/purposes (1) What intraoperative technical problems were observed during the first 2 years using navigation? (2) What was the mean time for navigation procedures and the time improvement during the learning curve? (3) Have there been any differences in the accuracy of the registration technique that occurred over time? (4) Did navigation achieve the goal of achieving a wide bone margin? Methods All patients who underwent preoperative virtual planning for tumor bone resections and operated on with navigation assistance from 2010 to 2012 were prospectively collected. Two surgeons (GLF, LAA-T) performed the intraoperative navigation assistance. Both surgeons had more than 5 years of experience in orthopaedic oncology with more than 60 oncology cases per year per surgeon. This study includes from the very first patients performed with navigation. Although they did not take any formal training in orthopaedic oncology navigation, both surgeons were trained in navigation for knee prostheses. Between 2010 and 2012, we performed 124 bone tumor resections; of these, 78 (63%) cases were resected using intraoperative navigation assistance. During this period, our general indications for use of navigation included pelvic and sacral tumors and those tumors that were reconstructed with massive bone allografts to obtain precise matching of the host and allograft osteotomies. Seventy-eight patients treated with this technology were included in the study. Technical problems (crashes) and time for the navigation procedure were reported after surgery. Accuracy of the registration technique was defined and the surgical margins of the removed specimen were determined by an experienced bone pathologist after the surgical procedure as intralesional, marginal, or wide margins. To obtain these data, we performed a chart review and review of operative notes. Results In four patients (of 78 [5%]), the navigation was not completed as a result of technical problems; all occurred during the first 20 cases of the utilization of this technology. The mean time for navigation procedures during the operation was 31 minutes (range, 11–61 minutes), and the early navigations took more time (the regression analysis shielded R2 = 0.35 with p\0.001). The median registration error was 0.6 mm (range, 0.3–1.1 mm). Registration did not improve over time (the regression analysis slope estimate is 0.014, with R2 = 0.026 and p = 0.15). Histological examinations of all specimens showed a wide bone tumor margin in all patients. However, soft tissue margins were wide in 58 cases and marginal in 20. Conclusions We conclude that navigation may be useful in achieving negative bony margins, but we cannot state that it is more effective than other means for achieving this goal. Technical difficulty precluded the use of navigation in 5% of cases in this series. Navigation time decreased with more experience in the procedure but with the numbers available, we did not improve the registration error over time. Given these observations and the increased time and expense of using navigation, larger studies are needed to substantiate the value of this technology for routine use. Level of Evidence Level IV, therapeutic study."

Browsing by Author "Milano, Federico E."

Results Per Page

Sort Options