Imaging Right Iliac Fossa (RIF) pain

Abdominal pain is one of the most common causes for referral to the emergency department coming second only after chest pain. The RIF is the most common location for abdominal pain. Clinical assessment offers little to as aid the diagnosis of RIF pain. With developments in ultrasound (US) and both spiral and multidetector computed tomography (CT), an accurate diagnosis can be made and unnecessary surgery and potentially lethal complications may be avoided.peer-reviewe

Prosper: image and robot-guided prostate brachytherapy

Brachytherapy for localized prostate cancer consists in destroying cancer by introducing iodine radioactive seeds into the gland through hollow needles. The planning of the position of the seeds and their introduction into the prostate is based on intra-operative ultrasound (US) imaging. We propose to optimize the global quality of the procedure by: i) using 3D US; ii) enhancing US data with MRI registration; iii) using a specially designed needle-insertion robot, connected to the imaging data. The imaging methods have been successfully tested on patient data while the robot accuracy has been evaluated on a realistic deformable phantom

Imaging groin hernias

Clinical differentiation of direct inguinal hernias, indirect inguinal hernias, femoral and Spigelian hernias can be difficult particularly with small hernias and in obese patients. Diagnostic imaging can detect and characterize hernias more reliably, allow better surgical planning and possibly even prevent unnecessary surgery. Detection of complications occurring in groin hernias is also of importance. Hernial incarceration is particularly evident on ultrasound (US) performed during rest and abdomimal straining (Valsalva maneuver) in both the supine and erect postures. Hernial strangulation is visible both with US and with computed tomography (CT) with fluid appearing around the hernial sac contents.peer-reviewe

Deep Learning for Accelerated Ultrasound Imaging

In portable, 3-D, or ultra-fast ultrasound (US) imaging systems, there is an increasing demand to reconstruct high quality images from limited number of data. However, the existing solutions require either hardware changes or computationally expansive algorithms. To overcome these limitations, here we propose a novel deep learning approach that interpolates the missing RF data by utilizing the sparsity of the RF data in the Fourier domain. Extensive experimental results from sub-sampled RF data from a real US system confirmed that the proposed method can effectively reduce the data rate without sacrificing the image quality.Comment: Invited paper for ICASSP 2018 Special Session for "Machine Learning in Medical Imaging: from Measurement to Diagnosis

Speckle filtering techniques for different quality level of healthy kidney ultrasound images

The increasing reliance of modern medicine on diagnostic techniques such as computerized tomography, histopathology, magnetic resonance imaging, radiology and ultrasound imaging shows the importance of medical images [1]. Ultrasound (US) imaging is an imaging technique that is far the least expensive and most portable comparing to other standard medical imaging modalities. US imaging is a safe technique, easy to use, noninvasive nature and provides real time imaging, hence it is used extensively. But on the downside, ultrasound imaging has a poor resolution of image compared with other medical imaging instrument like Magnetic Resonance Imaging (MRI). US has wide spread application as a primary diagnostic aid of obstetrics and gynecology, due to the lack of ionizing radiation or strong magnetic fields. General US imaging applications include soft tissue organ and carotid arter

Deep learning for cardiac image segmentation: A review

Deep learning has become the most widely used approach for cardiac image segmentation in recent years. In this paper, we provide a review of over 100 cardiac image segmentation papers using deep learning, which covers common imaging modalities including magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound (US) and major anatomical structures of interest (ventricles, atria and vessels). In addition, a summary of publicly available cardiac image datasets and code repositories are included to provide a base for encouraging reproducible research. Finally, we discuss the challenges and limitations with current deep learning-based approaches (scarcity of labels, model generalizability across different domains, interpretability) and suggest potential directions for future research

Penatalaksanaan Fisioterapi pada Kondisi Cervical Root Syndrome (CRS) di Rumah Sakit TK. II Dr. Soedjono Magelang

Cervical Root Syndrome (CRS) is a syndrome or disease characterized by compression of the nerve root resulting from protrusion or narrowing of the herniated disc. The usual effects of compression on the nerve root are the presence of pain that spreads or numbs from the neck to the arm. The method used is the provision of ultrasound (US), Transcutaneous electrical nerve stimulation (TENS)exercise therapy are evaluated using VDS for pain, Goneometer for LGS. to determine the benefits of ultrasound (US), Transcutaneous electrical nerve stimulation (TENS) and Exercise Therapy in case CERVICAL ROOT SYNDROME (CRS). after 6th therapy, the result of pain reduction, with VDS from FT0 to FT6 can be seen, the silent pain from FT0 to FT6 is same 1, whereas the tenderness from FT0 4 to FT6 becomes 2, motion pain from FT0 5 FT6 to 3. LGS with Goneometer increased flexion neck from FT0 8 cm to FT6 9cm extension neck from FT0 5cm to FT6 6cm, side fleksi dextra from FT0 10cm to FT6 11cm , the result of side fleksi sinistra from FT0 to FT6 is same 1cm, rotasi lateral dextra from FT0 13cm to FT6 14 cm, rotasi lateral sinistra from FT0 11cm to FT6 12cm Conclusion: 2 ultrasound (US), Transcutaneous electrical nerve stimulation (TENS) and Exercise Therapy modality can reduce pain, increase joint motion (LGS