An automatic classification method for distinguishing between indolent and clinically significant carcinoma using multiparametric MRI (mp-MRI) imaging is provided. By utilizing a convolutional neural network (CNN), which automatically extracts deep features, the hierarchical classification framework avoids deficiencies in current schemes in the art such as the need to provide handcrafted features predefined by a domain expert and the precise delineation of lesion boundaries by a human or computerized algorithm. This hierarchical classification framework is trained using previously acquired mp-MRI data with known cancer classification characteristics and the framework is applied to mp-MRI images of new patients to provide identification and computerized cancer classification results of a suspicious lesion.

The present disclosure relates to a method and a system for detecting an anomaly within a biological tissue. A first image of the biological tissue is obtained, the first image containing light at a first wavelength. A second image of the biological tissue is obtained, the second image containing light at a second wavelength. A texture analysis of the biological tissue is performed using spatial information of the first and second images. The texture analysis is resolved over the first and second wavelengths.

Disclosed herein is an apparatus comprising: an insertion tube configured to be inserted into a human; a metal target disposed inside the insertion tube and configured to emit X-ray by receiving radiation.

In a method for generating a surrogate marker based on medical image data mapping an image region, the medical image data is detected using a first interface, a first subregion of the image region is selected by segmenting a first structure included in the image region, a first property of the first subregion is extracted, the surrogate marker is determined based on the first property, and the surrogate marker is provided using a second interface.

The subject matter discussed herein relates to multi-modal image alignment to facilitate biopsy procedures and post-biopsy procedures. In one such example, prostate structures (or other suitable anatomic features or structures) are automatically segmented in pre-biopsy MR and pre-biopsy ultrasound images. Thereafter, pre-biopsy MR and pre-biopsy ultrasound contours are aligned. To account for non-linear deformation of the imaged anatomic structure, a patient-specific transformation model is trained via deep learning based at least in part on the pre-biopsy ultrasound images. The pre-biopsy ultrasound images that are overlaid with the pre-biopsy MR contours and based off the deformable transformation model are then aligned with the biopsy ultrasound images. Such real-time alignment using multi-modality imaging techniques provides guidance during the biopsy and post-biopsy system.

A method for detection and treatment of cancerous cells utilizes an infrared imaging device to capture a first infrared image of hot spots near a meridian pathway on the body. The hot spot may indicate irregularities in cells in the body. The meridian pathway acts as a channel to the interior of body, where cancerous cells may be active. A white spot indicates an irregularly hot cell, indicating potential cancer. A predetermined amount of solution that contains solid water particles is administered orally, intravenously or topically, every day for a long period of time.

In some examples, a medical system includes a medical device. The medical device may include a housing configured to be implanted in a target site of a patient, a light emitter configured to emit a signal configured to cause a fluorescent marker to emit a fluoresced signal into the target site, and a light detector that may be configured to detect the fluoresced signal. The medical system may include processing circuitry configured to determine a characteristic of the fluorescent marker based on the emitted signal and the fluoresced signal. The characteristic of the fluorescent marker may be indicative of a presence of a compound in the patient, and the processing circuitry may be configured to track the presence of the compound of the patient based on the characteristic of the fluorescent marker.

The present disclosure relates to compounds that are useful as near-infrared fluorescence probes, wherein the compounds include i) a pteroyl ligand that binds to a target receptor protein, ii) a dye molecule, and iii) a linker molecule that comprises an amino acid or derivative thereof. The disclosure further describes methods and compositions for incorporating the compounds as used for the targeted imaging of tumors. Conjugation of the amino acid linking groups increase specificity and detection of the compound. Methods and compositions for use thereof in diagnostic imaging are contemplated.

Methods and apparatus for computer-aided prostate condition diagnosis are disclosed. An example computer-aided prostate condition diagnosis apparatus includes memory to store instructions and a processor. The example processor can detect a lesion from an image of a prostate gland and generate a mapping of the lesion from the image to a sector map, the generating the mapping of the lesion comprising identifying a depth region of the lesion, wherein the depth region indicates a location of the lesion along a depth axis. The processor can also provide the sector map comprising a representation of the lesion within the prostate gland mapped from the image to the sector map.

The disclosed apparatus, systems and methods relate to devices, systems and methods for intra-operative imaging.